Artificial intelligence is being used successfully in several ways during the COVID-19 pandemic, including identifying disease clusters, monitoring cases, predicting future outbreaks and mortality risk, diagnosing COVID-19, and managing disease spread through resource allocation. It also facilitates training, record maintenance, and pattern recognition to study disease trends. AI can significantly improve treatment consistency and decision making by developing useful algorithms. It is helpful for both treating COVID-19 patients and properly monitoring their health.
This talk gives an introduction about Healthcare Use cases - The AI ladder and Lifestyle AI at Scale Themes The iterative nature of the workflow and some of the important components to be aware in developing AI health care solutions were being discussed. The different types of algorithms and when machine learning might be more appropriate in deep learning or the other way will also be discussed. Use cases in terms of examples are also shared as part of this presentation .
Artificial intelligence enters the medical fieldRuchi Jain
In the medical and health field, artificial intelligence can help reduce the cost of ongoing health operations, and can have an impact on the quality of medical care for patients everywhere. By diagnosing diseases earlier, AI can also improve patient outcomes. No matter how you look at it, artificial intelligence has great potential in healthcare.
Artificial intelligence in health care by Islam salama " Saimo#BoOm "Dr-Islam Salama
A Lecture about basics and concepts of Artificial Intelligence in health care & there applications
محاضرة عامة حول الذكاء الإصطناعي وأساسياته في الرعاية الصحية والطبية وتطبيقاته
Artificial Intelligence in Health Care 247 Labs Inc
This presentation was shown at the Artificial Intelligence in Health Care event in Toronto Nov 16 2017. The discussion was to introduce various applications of artificial intelligence and machine learning in the health care field.
This talk gives an introduction about Healthcare Use cases - The AI ladder and Lifestyle AI at Scale Themes The iterative nature of the workflow and some of the important components to be aware in developing AI health care solutions were being discussed. The different types of algorithms and when machine learning might be more appropriate in deep learning or the other way will also be discussed. Use cases in terms of examples are also shared as part of this presentation .
Artificial intelligence enters the medical fieldRuchi Jain
In the medical and health field, artificial intelligence can help reduce the cost of ongoing health operations, and can have an impact on the quality of medical care for patients everywhere. By diagnosing diseases earlier, AI can also improve patient outcomes. No matter how you look at it, artificial intelligence has great potential in healthcare.
Artificial intelligence in health care by Islam salama " Saimo#BoOm "Dr-Islam Salama
A Lecture about basics and concepts of Artificial Intelligence in health care & there applications
محاضرة عامة حول الذكاء الإصطناعي وأساسياته في الرعاية الصحية والطبية وتطبيقاته
Artificial Intelligence in Health Care 247 Labs Inc
This presentation was shown at the Artificial Intelligence in Health Care event in Toronto Nov 16 2017. The discussion was to introduce various applications of artificial intelligence and machine learning in the health care field.
The number of startups entering the healthcare AI space has increased in recent years, with over 50 companies raising their first equity rounds since January 2015. Deals to healthcare-focused AI startups went up from less than 20 in 2012 to nearly 70 in 2016.
10 Common Applications of Artificial Intelligence in HealthcareTechtic Solutions
List of 10 Common Applications of Artificial Intelligence that explain how artificial intelligence is used in healthcare and why it is necessary? To read briefly all common applications of artificial intelligence in healthcare then visit at https://www.techtic.com/blog/applications-of-ai-in-healthcare/
How Artificial Intelligence in Transforming PharmaTyrone Systems
Artificial intelligence in Pharma refers to the use of automated algorithms to perform tasks which traditionally rely on human intelligence. Over the last five years, the use of artificial intelligence in the pharma and biotech industry has redefined how scientists develop new drugs, tackle disease, and more.
Given the growing importance of Artificial Intelligence for the pharma industry, we wanted to create a comprehensive report which helps every business leader understand the biggest breakthroughs in the biotech space which are assisted by the deployment of artificial intelligence technologies.
Artificial Intelligence (AI) is nowadays used frequently in many application domains. Although sometimes considered only as an afterthought in the public discussion compared to other domains such as health, transportation, and manufacturing, the media domain is also transformed by AI enabling new opportunities, from content creation e.g. “robojournalism” and individualised content to optimisation of the content production and distribution. Underlaying many of these new opportunities is the use of AI in its current reincarnation as deep learning for understanding the audio-visual content by extracting structured information from the unstructured data, the audio-visual content.
In this talk the current understanding and trends of AI will therefore be discussed, what can be done, what is done, and what challenges remain in the use of AI especially in the context of media applications and services. The talk is not so much focused on the details and fundamentals of deep learning, but rather on a practical perspective on how recent advances in this field can be utilised in use-cases in the media domain, especially with respect to audio-visual content and in the broadcasting domain.
In this webinar, we will be covering what exactly an SaMDs, or Software as a Medical Device, and go over some examples with Artificial Intelligence. We will also look at Artificial Intelligence and Machine Learning versus the traditional software. Next, we will go into the regulatory framework for these types of software, then explain how EMMA International can help you get your SaMD to market.
Drug discovery and development is a long and expensive process and over time has notoriously bucked Moore’s law that it now has its own law called Eroom’s Law named after it (the opposite of Moore’s). It is estimated that the attrition rate of drug candidates is up to 96% and the average cost to develop a new drug has reached almost $2.5 billion in recent years. One of the major causes for the high attrition rate is drug safety, which accounts for 30% of the failures.
Even if a drug is approved in market, it could be withdrawn due to safety problems. Therefore, evaluating drug safety extensively as early as possible is paramount in accelerating drug discovery and development. This talk provides a high-level overview of the current process of rational drug design that has been in place for many decades and covers some of the major areas where the application of AI, Deep learning and ML based techniques have had the most gains.
Specifically, this talk covers a variety of drug safety related AI and ML based techniques currently in use which can generally divided into 3 main categories:
1. Discovery,
2. Toxicity and Safety, and
3. Post-Market Monitoring.
We will address the recent progress in predictive models and techniques built for various toxicities. It will also cover some publicly available databases, tools and platforms available to easily leverage them.
We will also compare and contrast various modeling techniques including deep learning techniques and their accuracy using recent research. Finally, the talk will address some of the remaining challenges and limitations yet to be addressed in the area of drug discovery and safety assessment.
AI for human communication is about recognition, parsing, understanding, and generating natural language. The concept of natural language is evolving. A key focus is the analysis, interpretation, and generation of verbal and written language. Other language focus areas include haptic, sonic, and visual language, data, and interaction.
Everything you want to know about role of artificial intelligence in drug discovery.
Artificial intelligence in health care and pharmacy, drug discovery, tensorflow, python,
deep neural network, GANs
AI in drug discovery and development
AI in clinical trials
The Amazing Ways Artificial Intelligence Is Transforming Genomics and Gene Ed...Bernard Marr
It is predicted that artificial intelligence (AI) will transform many aspects of our life including healthcare and genomics. AI and machine learning have helped us to understand the genome of organisms and will potentially change the way we treat disease, determine effective drugs and edit genes.
AI, Machine Learning Playing Important Role In Fighting COVID-19 OpenTeQ group
This is example of research at the Radiological Society of North America. Highlighting the point out this phenomenon- that some of the patients are falling ill and dying as some others are experiencing very mild symptoms are none at all is the most mysterious element of the disease. Mortality is one of the correlations with some of the major factors like age, gender, and other major chronic conditions. Hence, more factors can be prognostic as the young individuals have succumbed to the virus.
Artificial intelligence to fight against covid19saritamathania
Artificial intelligence (AI) and machine learning are playing a significant role in understanding and addressing the crisis caused by COVID-19. The technology mimic human intelligence and ingest great volumes of data to quickly chart patterns and identify insights.
One example is when BenevolentAI, a global leader in the development and application of artificial intelligence for drug discovery, took just few days to find that Baricitinib (a drug currently approved for rheumatoid arthritis, owned by Eli Lilly) is a strongest candidate and can be a potential treatment for COVID-19 patients.
This accelerated the clinical trials of #Baricitinib and Eli Lilly (a giant American Pharmaceutical company) has already commenced phase III clinical trials of Baricitinib to treat COVID-19.
Few more names include Deepmind, ImmunoPrecise, Insilico, healx, Imperial College, Tech Mahindra, and Deargen. Some Indian companies include NIRAMAI, Staqu, Qure.AI, Tech Mahindra, and DiyCam.
The number of startups entering the healthcare AI space has increased in recent years, with over 50 companies raising their first equity rounds since January 2015. Deals to healthcare-focused AI startups went up from less than 20 in 2012 to nearly 70 in 2016.
10 Common Applications of Artificial Intelligence in HealthcareTechtic Solutions
List of 10 Common Applications of Artificial Intelligence that explain how artificial intelligence is used in healthcare and why it is necessary? To read briefly all common applications of artificial intelligence in healthcare then visit at https://www.techtic.com/blog/applications-of-ai-in-healthcare/
How Artificial Intelligence in Transforming PharmaTyrone Systems
Artificial intelligence in Pharma refers to the use of automated algorithms to perform tasks which traditionally rely on human intelligence. Over the last five years, the use of artificial intelligence in the pharma and biotech industry has redefined how scientists develop new drugs, tackle disease, and more.
Given the growing importance of Artificial Intelligence for the pharma industry, we wanted to create a comprehensive report which helps every business leader understand the biggest breakthroughs in the biotech space which are assisted by the deployment of artificial intelligence technologies.
Artificial Intelligence (AI) is nowadays used frequently in many application domains. Although sometimes considered only as an afterthought in the public discussion compared to other domains such as health, transportation, and manufacturing, the media domain is also transformed by AI enabling new opportunities, from content creation e.g. “robojournalism” and individualised content to optimisation of the content production and distribution. Underlaying many of these new opportunities is the use of AI in its current reincarnation as deep learning for understanding the audio-visual content by extracting structured information from the unstructured data, the audio-visual content.
In this talk the current understanding and trends of AI will therefore be discussed, what can be done, what is done, and what challenges remain in the use of AI especially in the context of media applications and services. The talk is not so much focused on the details and fundamentals of deep learning, but rather on a practical perspective on how recent advances in this field can be utilised in use-cases in the media domain, especially with respect to audio-visual content and in the broadcasting domain.
In this webinar, we will be covering what exactly an SaMDs, or Software as a Medical Device, and go over some examples with Artificial Intelligence. We will also look at Artificial Intelligence and Machine Learning versus the traditional software. Next, we will go into the regulatory framework for these types of software, then explain how EMMA International can help you get your SaMD to market.
Drug discovery and development is a long and expensive process and over time has notoriously bucked Moore’s law that it now has its own law called Eroom’s Law named after it (the opposite of Moore’s). It is estimated that the attrition rate of drug candidates is up to 96% and the average cost to develop a new drug has reached almost $2.5 billion in recent years. One of the major causes for the high attrition rate is drug safety, which accounts for 30% of the failures.
Even if a drug is approved in market, it could be withdrawn due to safety problems. Therefore, evaluating drug safety extensively as early as possible is paramount in accelerating drug discovery and development. This talk provides a high-level overview of the current process of rational drug design that has been in place for many decades and covers some of the major areas where the application of AI, Deep learning and ML based techniques have had the most gains.
Specifically, this talk covers a variety of drug safety related AI and ML based techniques currently in use which can generally divided into 3 main categories:
1. Discovery,
2. Toxicity and Safety, and
3. Post-Market Monitoring.
We will address the recent progress in predictive models and techniques built for various toxicities. It will also cover some publicly available databases, tools and platforms available to easily leverage them.
We will also compare and contrast various modeling techniques including deep learning techniques and their accuracy using recent research. Finally, the talk will address some of the remaining challenges and limitations yet to be addressed in the area of drug discovery and safety assessment.
AI for human communication is about recognition, parsing, understanding, and generating natural language. The concept of natural language is evolving. A key focus is the analysis, interpretation, and generation of verbal and written language. Other language focus areas include haptic, sonic, and visual language, data, and interaction.
Everything you want to know about role of artificial intelligence in drug discovery.
Artificial intelligence in health care and pharmacy, drug discovery, tensorflow, python,
deep neural network, GANs
AI in drug discovery and development
AI in clinical trials
The Amazing Ways Artificial Intelligence Is Transforming Genomics and Gene Ed...Bernard Marr
It is predicted that artificial intelligence (AI) will transform many aspects of our life including healthcare and genomics. AI and machine learning have helped us to understand the genome of organisms and will potentially change the way we treat disease, determine effective drugs and edit genes.
AI, Machine Learning Playing Important Role In Fighting COVID-19 OpenTeQ group
This is example of research at the Radiological Society of North America. Highlighting the point out this phenomenon- that some of the patients are falling ill and dying as some others are experiencing very mild symptoms are none at all is the most mysterious element of the disease. Mortality is one of the correlations with some of the major factors like age, gender, and other major chronic conditions. Hence, more factors can be prognostic as the young individuals have succumbed to the virus.
Artificial intelligence to fight against covid19saritamathania
Artificial intelligence (AI) and machine learning are playing a significant role in understanding and addressing the crisis caused by COVID-19. The technology mimic human intelligence and ingest great volumes of data to quickly chart patterns and identify insights.
One example is when BenevolentAI, a global leader in the development and application of artificial intelligence for drug discovery, took just few days to find that Baricitinib (a drug currently approved for rheumatoid arthritis, owned by Eli Lilly) is a strongest candidate and can be a potential treatment for COVID-19 patients.
This accelerated the clinical trials of #Baricitinib and Eli Lilly (a giant American Pharmaceutical company) has already commenced phase III clinical trials of Baricitinib to treat COVID-19.
Few more names include Deepmind, ImmunoPrecise, Insilico, healx, Imperial College, Tech Mahindra, and Deargen. Some Indian companies include NIRAMAI, Staqu, Qure.AI, Tech Mahindra, and DiyCam.
AI and covid19 | Mr. R. Rajkumar, Assistant Professor, Department of CSERajkumar R
SRM Institute of Science and Technology Directorate of Research presents Webinars on various domains. This is the slide presented by Mr. R. Rajkumar, Assistant Professor, Department of CSE,
No doubt, #healthcare is one of the most promising applications for #AI. This #technology can offer lots of benefits for this sector: it can help Health institutions to cut costs by lowering readmission rates, it can help insurance companies to optimize their risk management techniques, and it can also help doctors find new ways of healing.
Follow the link and learn more: https://indatalabs.com/blog/machine-learning-in-healthcare
Dissertation on Computer Science: Machine Learning Algorithm to Predict Covid...PhD Assistance
Artificial intelligence and data science play a vital role in the health-care business in this era of automation. Medical practitioners may simply manage their duties and patient care since these technologies is so well-connected. Dependence on automated systems such as AI has increased in healthcare services.ML can identify illness and viral infections more precisely, allowing patients’ ailments to be identified earlier, severe phases of diseases to be avoided, and fewer people to be treated.
Read More: https://bit.ly/3HGu9NY
For Enquiry:
India: +91 91769 66446
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Email: info@phdassistance.com
Dissertation on Computer Science: Machine Learning Algorithm to Predict Covid...PhD Assistance
Artificial intelligence and data science play a vital role in the health-care business in this era of automation. Medical practitioners may simply manage their duties and patient care since these technologies is so well-connected. Dependence on automated systems such as AI has increased in healthcare services.ML can identify illness and viral infections more precisely, allowing patients’ ailments to be identified earlier, severe phases of diseases to be avoided, and fewer people to be treated.
Read More: https://bit.ly/3HGu9NY
For Enquiry:
India: +91 91769 66446
UK: +44 7537144372
Email: info@phdassistance.com
Nobody can predict the future, however by following trends, we can navigate the direction in which we’re heading. Trends are dictated by a wide range of economic and political factors, and often they are propelled by innovations. The newest technological trends owe themselves to necessary innovations in the healthcare industry, spurred by the Covid-19 pandemic.
With the Covid-19 pandemic revealing the gaps and inefficiencies of healthcare systems around the world, the newest developments in healthcare technologies are suddenly getting a lot more attention. This is useful, because the executives who are often hesitant in changing long-standing healthcare practices must revaluate and evolve in order to provide the most effective treatment plans for their patients.
How machine learning is used to find the covid 19 vaccineValiant Technosoft
Let us understand the concept by taking an example of the deadliest pandemic of coronavirus. Machine Learning algorithms may help in detecting the severity of coronavirus in patients having the doubt of this deadly disease.
https://valianttechnosoft.com/blog/how-machine-learning-is-used-to-find-the-coronavirus-vaccine/
Healthcare AI will undoubtedly become one of the fastest growing industries in the industry. Although the medical and health artificial intelligence industry was valued at US$ 600 million in 2014 , it is expected to reach a staggering US$ 150 billion by 2026. There are countless AI applications in the healthcare industry, let’s look at some outstanding ones.
Precision Algorithms in Healthcare: Improving treatments with AIDay1 Technologies
It’s 2020 and we can safely say that the year hasn’t been our best or what we wanted it to be like. The alarming spread of COVID-19, and its aftermath has people unrooted and shaken to their toes, and literally everyone is looking at technology and healthcare innovations to find an answer to the pandemic. And fast.
Digital technology and COVID-19
The past decade has allowed the development of a multitude of digital tools. Now they can be used to remediate the COVID-19 outbreak.
Daniel Shu Wei Ting, Lawrence Carin, Victor Dzau and Tien Y. Wong, publicado en Nature Medicine.
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
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These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
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Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
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Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
4. INTRODUCTION
The world has been coping with stressful times and Artificial
Intelligence technology is a ray of hope that would help us to fight
the pandemic with high spirits.
The measures, if taken seriously, can do wonders while coming out of
the bright side of the tunnel.
This might turn out to be a revolutionizing moment in the field of
Artificial Intelligence (AI )technology as its implications in these times
might result in excessive use of it and thus, furthering the increase of
career scope in this domain.
5. Covid -19 and artificial intelligence
There are six areas where AI can contribute to the fight against
COVID-19:
i) early warnings and alerts
ii) tracking and prediction
iii) data dashboards
iv) diagnosis and prognosis
v) treatments, and cures
vi) social control.
6.
7. Development of drugs and vaccines:
Artificial Intelligence (AI) is used for drug research by analyzing the available
data on COVID-19.
It is useful for drug delivery design and development.
This technology is used in speeding up drug testing in real-time, where
standard testing takes plenty of time and hence helps to accelerate this
process significantly, which may not be possible by a human .
It can help to identify useful drugs for the treatment of COVID-19 patients. It
has become a powerful tool for diagnostic test designs and vaccination
development .
AI helps in developing vaccines and treatments at much of faster rate than
usual and is also helpful for clinical trials during the development of the
vaccine.
8. Disease Monitoring
Since the virus is crucial enough to be spread through human contact
and migration, it has become imperative that we keep surveillance
around the world.
Artificial Intelligence (AI )can build an intelligent platform for
automatic monitoring and prediction of the spread of this virus.
A neural network can also be developed to extract the visual features
of this disease, and this would help in proper monitoring and
treatment of the affected individuals .
It has the capability of providing day-to-day updates of the patients
and also to provide solutions to be followed in COVID-19 pandemic.
9. Contact tracing of the individuals
Artificial Intelligence (AI) can help analyze the level of infection by this virus
identifying the clusters and ‘hot spots’ and can successfully do the contact
tracing of the individuals and also to monitor them. It can predict the future
course of this disease and likely reappearance.
10.
11. Projection of cases and mortality
This technology can track and forecast the nature of the virus from the
available data, social media and media platforms, about the risks of the
infection and its likely spread. Further, it can predict the number of positive
cases and death in any region. Artificial Intelligence (AI )can help identify the
most vulnerable regions, people and countries and take measures
accordingly.
12. Reducing the workload of healthcare
workers
Due to a sudden and massive increase in the numbers of patients during
COVID-19 pandemic, healthcare professionals have a very high workload.
Here, Artificial Intelligence (AI )is used to reduce the workload of healthcare
workers .
It helps in early diagnosis and providing treatment at an early stage using
digital approaches and decision science, offers the best training to students
and doctors regarding this new disease .
Artificial Intelligence (AI) can impact future patient care and address more
potential challenges which reduce the workload of the doctors.
13. Deployment of Robots and Drones
One of the important revelations of AI has been the
manufacturing of robots and drones.
The drones are also used to keep a check on the larger
audience and to disinfect public places.
Robots have been deployed for facilitating food and
medication deliveries.
This has been helpful in providing risk-free medical care
for healthcare workers and to contain the spread of virus
amongst humans.
14. Curative Drug Research
Artificial Intelligence has marked a difference by using the algorithms
to develop the molecular structure to prepare curable drugs for
fighting COVID-19 in the coming future.
artificial intelligence (AI)can be helpful in the manufacturing of
antibodies and vaccines.
Google’s artificial intelligence (AI )company, DeepMind has initiated
to process out the structural models of proteins in order to be of
assistance in the understanding of the nitty-gritty of the virus.
18. Summary
artificial intelligence (AI )is being successfully used
identification of disease clusters
monitoring of cases
prediction of the future outbreaks
mortality risk
diagnosis of COVID-19
disease management by resource allocation
Facilitating training, record maintenance and pattern recognition for
studying the disease trend.
20. Conclusion
1-Artificial Intelligence is an upcoming and useful tool to identify early infections
due to coronavirus and also helps in monitoring the condition of the infected
patients.
2- It can significantly improve treatment consistency and decision making by
developing useful algorithms.
3- Artificial Intelligence (AI )is not only helpful in the treatment of COVID-
19infected patients but also for their proper health monitoring. It can track the
crisis of COVID-19 at different scales such as medical, molecular and
epidemiological applications.
4-It is also helpful to facilitate the research on this virus using analyzing the
available data.
5-Artificial Intelligence (AI) can help in developing proper treatment regimens,
prevention strategies, drug and vaccine development.
21. REFFERENCES
1-Artificial Intelligence (AI) applications for COVID-19 pandemic. Raju
Vaishya a, Mohd Javaid b, *, Ibrahim Haleem Khan c, Abid Haleem .Diabetes
& Metabolic Syndrome: Clinical Research & Reviews Volume 14, Issue 4, July–
August 2020, Pages 337-339
2-Application of Artificial Intelligence in COVID-19 drug repurposing Sweta
Mohanty a, Md Harun AI Rashid b, Mayank Mridul c, Chandana Mohanty a, *,
Swati Swayamsiddha d. Diabetes & Metabolic Syndrome: Clinical Research &
Reviews Volume 14, Issue 5, September–October 2020, Pages 1027-1031
22. 3-Applications of machine learning and artificial intelligence for Covid-19 (SARS-
CoV-2) pandemic: A review Samuel Lalmuanawmaa,∗, Jamal Hussaina , Lalrinfela
Chhakchhuak b. Chaos, Solitons & FractalsVolume 139, October 2020, 110059.
4-The role of artificial intelligence in tackling COVID-19. Neelima Arora*,1, Amit K
Banerjee2 & Mangamoori L Narasu1. 10.2217/fvl-2020-0130 C 2020 Future
Medicine Ltd.
5-Approaches Based on Artificial Intelligence and the Internet of Intelligent
Things to Prevent the Spread of COVID-19: Scoping Review. Aya Sedky Adly, MSc,
PhD,1 Afnan Sedky Adly, MSc,2,3 and Mahmoud Sedky Adly, DDS, MSc, HDD. J
Med Internet Res. 2020 Aug; 22(8): e19104.