Direct terminology binding allows nodes in archetypes and templates to be bound to specific terms or term sets. However, direct binding has issues including incomplete terminology coverage and requiring terminology expertise. Guidance suggests concentrating on current requirements, using internal value sets, and adding external bindings where needed. Term set binding applies constraints at the template level but usually requires an "out clause" to allow for flexibility. Examples show binding nodes for family history information to appropriate SNOMED CT and local terminology terms and term sets.
Linkages to EHRs and Related Standards. What can we learn from the Parallel U...Koray Atalag
This is the prezo I used during the CellML workshop in Waiheke Island, Auckland, New Zealand on 13 April 2015. The aim was to introduce information modelling methods and tools for the purpose of inspiring computational modelling work in the area of semantics and interoperability.
https://telecombcn-dl.github.io/2018-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
The Logical Model Designer - Binding Information Models to TerminologySnow Owl
This presentation demonstrates the functionality provided by the Logical Model Designer (LMD) and Snow Owl tools, which enables terminology to be bound to the Singapore Logical Information Model.
Abstract:
A critical enabler in the journey towards semantic interoperability in Singapore is the Singapore "˜Logical Information Model' (LIM). The LIM is a model of the healthcare information shared within Singapore, and is defined as a set of reusable "˜archetypes' for each clinical concept (e.g. Problem/Diagnosis, Pharmacy Order). These archetypes are then constrained and composed into "˜templates' to support specific use cases.
The Singapore LIM harmonises the semantics of the information structures with the terminology, using multiple types of terminology bindings, including semantic, value domain and constraint bindings. Value domain bindings are defined to both national "˜reference terminology' (used for querying nationally-collated data), as well as to a variety of "˜interface terminologies' used within local clinical systems (required to enforce conformance-compliance rules over message specifications generated from the LIM). To support the diversity of pre-coordination captured in local interface terms, "˜design patterns' are included in the LIM, based on the SNOMED CT concept model. These design patterns represent a logical model of meaning for a specific concept, and allow more than one split between the information model and the terminology model to be represented in a semantically-consistent manner.
This presentation will demonstrate the "˜Logical Model Designer' (LMD) - an Eclipse-based tool that is being used to maintain Singapore's Logical Information Model. A number of features of the LMD tooling will be demonstrated, with a specific focus on how the information structure is bound to the terminology via an interface to the Snow Owl platform. Value Domains are defined as reference sets within Snow Owl and then linked to the information structures defined in the LMD.
Please see our website http://b2i.sg for further information.
Statistical Physics of Ecological Networks: from patterns to principlesSamir Suweis
Talk that I gave in Leeds at the school of Mathematics on 26/11/2014. It is an overview of my recent on research on mutualistic ecological networks by using tools and approaches from statistical physics.
DWPI Markush Database on STN – A New Perspective for Searching Markush Struct...Dr. Haxel Consult
Searching for Markush structures has been a rather difficult task especially since it was necessary in the past to work with different retrieval systems. With the new implementation of the DWPI Markush database from Thomson Reuters on STN it is now possible to search for Markush structures using a single structure query for all structure databases. In this system the structure and bibliographic databases are integrated within a content domain which allows easy and fast projections between the databases. It will be shown that the DWPI Markush concept of superatoms can be integrated in the STN query system, allowing users to exploit the full potential of the DWPI Markush data. To enable complete and high precision searches it was necessary to develop a new Markush search engine. Improved evaluation of Markush structures is possible with hit structure display, highlighting, and assembled structures. Based on this implementation it will be possible to develop further innovative features in the future.
Linkages to EHRs and Related Standards. What can we learn from the Parallel U...Koray Atalag
This is the prezo I used during the CellML workshop in Waiheke Island, Auckland, New Zealand on 13 April 2015. The aim was to introduce information modelling methods and tools for the purpose of inspiring computational modelling work in the area of semantics and interoperability.
https://telecombcn-dl.github.io/2018-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or image captioning.
The Logical Model Designer - Binding Information Models to TerminologySnow Owl
This presentation demonstrates the functionality provided by the Logical Model Designer (LMD) and Snow Owl tools, which enables terminology to be bound to the Singapore Logical Information Model.
Abstract:
A critical enabler in the journey towards semantic interoperability in Singapore is the Singapore "˜Logical Information Model' (LIM). The LIM is a model of the healthcare information shared within Singapore, and is defined as a set of reusable "˜archetypes' for each clinical concept (e.g. Problem/Diagnosis, Pharmacy Order). These archetypes are then constrained and composed into "˜templates' to support specific use cases.
The Singapore LIM harmonises the semantics of the information structures with the terminology, using multiple types of terminology bindings, including semantic, value domain and constraint bindings. Value domain bindings are defined to both national "˜reference terminology' (used for querying nationally-collated data), as well as to a variety of "˜interface terminologies' used within local clinical systems (required to enforce conformance-compliance rules over message specifications generated from the LIM). To support the diversity of pre-coordination captured in local interface terms, "˜design patterns' are included in the LIM, based on the SNOMED CT concept model. These design patterns represent a logical model of meaning for a specific concept, and allow more than one split between the information model and the terminology model to be represented in a semantically-consistent manner.
This presentation will demonstrate the "˜Logical Model Designer' (LMD) - an Eclipse-based tool that is being used to maintain Singapore's Logical Information Model. A number of features of the LMD tooling will be demonstrated, with a specific focus on how the information structure is bound to the terminology via an interface to the Snow Owl platform. Value Domains are defined as reference sets within Snow Owl and then linked to the information structures defined in the LMD.
Please see our website http://b2i.sg for further information.
Statistical Physics of Ecological Networks: from patterns to principlesSamir Suweis
Talk that I gave in Leeds at the school of Mathematics on 26/11/2014. It is an overview of my recent on research on mutualistic ecological networks by using tools and approaches from statistical physics.
DWPI Markush Database on STN – A New Perspective for Searching Markush Struct...Dr. Haxel Consult
Searching for Markush structures has been a rather difficult task especially since it was necessary in the past to work with different retrieval systems. With the new implementation of the DWPI Markush database from Thomson Reuters on STN it is now possible to search for Markush structures using a single structure query for all structure databases. In this system the structure and bibliographic databases are integrated within a content domain which allows easy and fast projections between the databases. It will be shown that the DWPI Markush concept of superatoms can be integrated in the STN query system, allowing users to exploit the full potential of the DWPI Markush data. To enable complete and high precision searches it was necessary to develop a new Markush search engine. Improved evaluation of Markush structures is possible with hit structure display, highlighting, and assembled structures. Based on this implementation it will be possible to develop further innovative features in the future.
Apoyo a la toma de decisiones clínicas con openEHR y SNOMED CT - casos de uso...Pablo Pazos
Taller dónde se demuestran los beneficios de implementar sistemas de información en salud basados en estándares, que permiten utilizar la información clínica existente para implementar mecanismos que aporten para tomar mejores decisiones clínicas.
Presentación informativa de qué es openEHR, para qué sirve en el contexto de los sistemas de información en salud, qué relación tiene con otros estándares y especificaciones, y cuáles son las nuevas especificaciones que se agregaron al estándar.
CaboLabs - Workshop de interoperabilidad usando estándaresPablo Pazos
Tercera charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
CaboLabs - Estándares e interoperabilidad en informática en saludPablo Pazos
Segunda charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
CaboLabs - Proyectos de informatica en saludPablo Pazos
Primera charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
Presentacion del programa de formacion profesional de Informática en Salud, E...Pablo Pazos
El video de la presentación puede verse aquí: https://www.youtube.com/watch?v=68kjzhc50Zs
Más información sobre cursos y talleres: http://cabolabs.com/es/capacitacion
openEHR: aspectos de interoperabilidad y mantenibilidadPablo Pazos
Presentación para el evento Information and Communication Technologies and Mobile Health: Lessons Learned and Challenges for Latin America and the world 2015. Lima, Perú.
Generación automática de interfaces de usuario para sistemas de información c...Pablo Pazos
Trabajo sobre generación automática de interfaces de usuario para sistemas de información en salud, basados en el estándar abierto openEHR. INFOLAC 2014, Montevideo, Uruguay.
Taller de implementación de openEHR - HIBA 2013Pablo Pazos
Taller de implementación de openEHR donde mostramos algunas herramientas que implementan el estándar, a modo de entender cómo y para qué se puede utilizar.
Las herramientas que vimos fueron desarrolladas en CaboLabs.com y son open source. Estas herramientas siguen una arquitectura orientada a servicios y fueron implementadas sobre tecnologías Java/Groovy/Grails.
Por un lado vimos una aplicación de registro clínico generada sobre EHRGen Framework. Y por otro lado un servidor de registros clínicos compartidos, EHRServer, donde vimos cómo crear consultas para obtener datos.
Todo con openEHR y arquetipos.
CaboLabs: expertos en informática médica, estándares e interoperabilidadPablo Pazos
Esta presentación es un resumen de nuestros servicios y experiencia en proyectos. Tanto de capacitación, como de consultoría e investigación y desarrollo.
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
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.
Apoyo a la toma de decisiones clínicas con openEHR y SNOMED CT - casos de uso...Pablo Pazos
Taller dónde se demuestran los beneficios de implementar sistemas de información en salud basados en estándares, que permiten utilizar la información clínica existente para implementar mecanismos que aporten para tomar mejores decisiones clínicas.
Presentación informativa de qué es openEHR, para qué sirve en el contexto de los sistemas de información en salud, qué relación tiene con otros estándares y especificaciones, y cuáles son las nuevas especificaciones que se agregaron al estándar.
CaboLabs - Workshop de interoperabilidad usando estándaresPablo Pazos
Tercera charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
CaboLabs - Estándares e interoperabilidad en informática en saludPablo Pazos
Segunda charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
CaboLabs - Proyectos de informatica en saludPablo Pazos
Primera charla de la jornada sobre estándares en informática en salud para Chiletec. https://informatica-medica.blogspot.com.uy/2017/10/chiletec-programa-de-difusion.html
Presentacion del programa de formacion profesional de Informática en Salud, E...Pablo Pazos
El video de la presentación puede verse aquí: https://www.youtube.com/watch?v=68kjzhc50Zs
Más información sobre cursos y talleres: http://cabolabs.com/es/capacitacion
openEHR: aspectos de interoperabilidad y mantenibilidadPablo Pazos
Presentación para el evento Information and Communication Technologies and Mobile Health: Lessons Learned and Challenges for Latin America and the world 2015. Lima, Perú.
Generación automática de interfaces de usuario para sistemas de información c...Pablo Pazos
Trabajo sobre generación automática de interfaces de usuario para sistemas de información en salud, basados en el estándar abierto openEHR. INFOLAC 2014, Montevideo, Uruguay.
Taller de implementación de openEHR - HIBA 2013Pablo Pazos
Taller de implementación de openEHR donde mostramos algunas herramientas que implementan el estándar, a modo de entender cómo y para qué se puede utilizar.
Las herramientas que vimos fueron desarrolladas en CaboLabs.com y son open source. Estas herramientas siguen una arquitectura orientada a servicios y fueron implementadas sobre tecnologías Java/Groovy/Grails.
Por un lado vimos una aplicación de registro clínico generada sobre EHRGen Framework. Y por otro lado un servidor de registros clínicos compartidos, EHRServer, donde vimos cómo crear consultas para obtener datos.
Todo con openEHR y arquetipos.
CaboLabs: expertos en informática médica, estándares e interoperabilidadPablo Pazos
Esta presentación es un resumen de nuestros servicios y experiencia en proyectos. Tanto de capacitación, como de consultoría e investigación y desarrollo.
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
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.
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
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.
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.
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!
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
263778731218 Abortion Clinic /Pills In Harare ,ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group of receptionists, nurses, and physicians have worked together as a teamof receptionists, nurses, and physicians have worked together as a team wwww.lisywomensclinic.co.za/
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
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
2. Terminology binding patterns
• Direct node‐binding
– e.g. ‘Urine color’ node
• Node name e.g.. “Urine color”
– Automatically has unique internal term ‘at0007’
– Can be ‘run‐time’ coded by external term
– Can be ‘run‐time’ mapped to an external term
• Node value e.g.. ‘Red, yellow, purple’
– Unique term provided by Internal value set ‘at0009’
– External term mapped to term from Internal value set
– External term used as the value
3. Direct‐binding issues
• Incomplete terminology / translation coverage
– e.g.. SNOMED
– 50‐70% for histopathology
• Effort
– Requires very good terminology skills
• Can be challenging to choose correct bindings
– Some concepts require post‐coordination to capture
correctly
– Is it worth trying to achieve complete node binding?
5. Direct‐binding guidance
• Concentrate on current requirements
– Archetypes and templates ‘fix’ the semantics
• Initial efforts guided by actual requirements
• More bindings can be added later as requirements
evolve
– Node bindings
• Use internal value sets. Consider leaving ‘open to allow
for local variation.
• Add External terminology bindings where required and
available
6. Termset‐binding issues
• Very little at Archetype‐level
– Scope of the termset binding is often too broad to
be meaningful at implementation
• E.g. ‘All procedures’ in ACTION.procedure archetype
– Very few examples of sensible termset‐bindings in
international archetypes
– Much more applicable at national level
• esp. National terminologies
7. Termset‐binding guidance
• Almost all at Template‐level
– Layered constraint approach
• All procedures
– Orthopedic procedures
» Knee specialist procedures
– But generally have to provide option to override
the constraint for unusual clinical situations
• e.g.. Non‐orthopedic procedure carried out in
Orthopedic department.
8. Termset‐binding guidance
• Microsoft / NHS Common User Interface
(CUI)
– Layered constraint with ‘termset filters
– ‘Get‐out clause’ where constraint is too tight
10. Example: “Family history”
Term bound to node Name
? 371534008 |Summary report (record artifact)
? 422735006 |Summary clinical document (record artifact)
Termset-bound to node Value: (Is_a genetic relation)
444148008 | Person in family of subject
Term bound to node Name:
408732007 | Subject Term bound to node internal Value set:
relationship context
[at0004|Not known] =365873007|Gender unknown (finding)
(attribute) [at0004|Not known] =UNK|Gender unknown
[at0005|Male] = SNOMEDCT::248153007 | Male (finding)
[at0005|Male] = KITH-SEX::M| Male
[at0006|Female] = 248152002 | Female(finding)
[at0006|Female] = KITH-SEX::F | Female
Term bound to node Name:
184100006 | Patient sex
(observable entity OR
Termset-bound to node Value: (??????)
429019009 | Finding related to biological sex