Liberating facts from the scientific literature - Jisc Digifest 2016 TheContentMine
Published on Mar 4, 2016 by PMR
Text and data mining (TDM) techniques can be applied to a wide range of materials, from published research papers, books and theses, to cultural heritage materials, digitised collections, administrative and management reports and documentation, etc. Use cases include academic research, resource discovery and business intelligence.
This workshop will show the value and benefits of TDM techniques and demonstrate how ContentMine aims to liberate 100,000,000 facts from the scientific literature, and ContentMine will provide a hands on demo on a topical and accessible scientific/medical subject.
Automatic Extraction of Science and Medicine from the scholarly literaturepetermurrayrust
Many scientists have to extract many facts out the scholarly literature - to evaluate other work or to extract useful collections of facts. This shows the approach, especially for systematic reviews of animal or clinical trials
Published on Jan 29, 2016 by PMR
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuous Integration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of content mining (TDM)
Automatic Extraction of Knowledge from the Literaturepetermurrayrust
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Published on Feb 29, 2016 by PMR
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Automatic Extraction of Knowledge from Biomedical literaturepetermurrayrust
a plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Liberating facts from the scientific literature - Jisc Digifest 2016 TheContentMine
Published on Mar 4, 2016 by PMR
Text and data mining (TDM) techniques can be applied to a wide range of materials, from published research papers, books and theses, to cultural heritage materials, digitised collections, administrative and management reports and documentation, etc. Use cases include academic research, resource discovery and business intelligence.
This workshop will show the value and benefits of TDM techniques and demonstrate how ContentMine aims to liberate 100,000,000 facts from the scientific literature, and ContentMine will provide a hands on demo on a topical and accessible scientific/medical subject.
Automatic Extraction of Science and Medicine from the scholarly literaturepetermurrayrust
Many scientists have to extract many facts out the scholarly literature - to evaluate other work or to extract useful collections of facts. This shows the approach, especially for systematic reviews of animal or clinical trials
Published on Jan 29, 2016 by PMR
Keynote talk to LEARN (LERU/H2020 project) for research data management. Emphasizes that problems are cultural not technical. Promotes modern approaches such as Git / continuous Integration, announces DAT. Asserts that the Right to Read in the Right to Mine. Calls for widespread development of content mining (TDM)
Automatic Extraction of Knowledge from the Literaturepetermurrayrust
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Published on Feb 29, 2016 by PMR
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Automatic Extraction of Knowledge from Biomedical literaturepetermurrayrust
a plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus.
Three slides have embedded movies - these do not show in slideshare and a first pass of this can be seen as a single file at https://vimeo.com/154705161
Automatic Extraction of Knowledge from Biomedical literature TheContentMine
Published on Mar 16, 2016 by PMR
A plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Talk to OpenForum Academy (Open Forum Europe) about Text and data Mining. Four use cases selected fo non-scientists. Also discussion of latest on Europena copyright reform and TDM exceptions
Published on Feb 07, 2016 by PMR
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus. Includes clips of the software in action
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
Amanuens.is HUmans and machines annotating scholarly literaturepetermurrayrust
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
High throughput mining of the scholarly literature TheContentMine
Published on Jun 7, 2016 by PMR
Talk given to statisticians in Tilburg, with emphasis on scholarly comms for detecting unusual features. Includes demo of Amanuens.is and image mining
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Can Computers understand the scientific literature (includes compscie material)TheContentMine
Published on Jan 24, 2014 by PMR
With the semantic web machines can autonomously carry out many knowledge-based tasks as well as humans. The main problems are not technical but the prevention of access to information. I advocate automatic downloading and indexing of all scientific information
Amanuens.is HUmans and machines annotating scholarly literature TheContentMine
Published on May 19, 2016 by PMR
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Mining the scientific literature for plants and chemistrypetermurrayrust
ContentMine can read the daily scientific literature and extract facts. This talk was given to the OpenPlant project - with whom ContentMine collaborate at a meeting on 2016-07-25/27 in Norwich. Examples of extracted facts are given.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus.
Three slides have embedded movies - these do not show in slideshare and a first pass of this can be seen as a single file at https://vimeo.com/154705161
Automatic Extraction of Knowledge from Biomedical literature TheContentMine
Published on Mar 16, 2016 by PMR
A plenary lecture to Cochrane Collaboration in Birmingham, on the value of automatically extracting knowledge. Covers the Why? How? What? Who? and problems and invites collaboration
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
An overview of Text and Data Mining (ContentMining) including live demonstrations. The fundamentals: discover, scrape, normalize , facet/index, analyze, publish are exemplified using the recent Zika outbreak. Mining covers textual and non-textual content and examples of chemistry and phylogenetic tress are given.
Talk to OpenForum Academy (Open Forum Europe) about Text and data Mining. Four use cases selected fo non-scientists. Also discussion of latest on Europena copyright reform and TDM exceptions
Published on Feb 07, 2016 by PMR
Use of ContentMine tools on the Open Access subset of EuropePubMedCentral to discover new knowledge about the Zika virus. Includes clips of the software in action
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
Amanuens.is HUmans and machines annotating scholarly literaturepetermurrayrust
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
High throughput mining of the scholarly literature TheContentMine
Published on Jun 7, 2016 by PMR
Talk given to statisticians in Tilburg, with emphasis on scholarly comms for detecting unusual features. Includes demo of Amanuens.is and image mining
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Can Computers understand the scientific literature (includes compscie material)TheContentMine
Published on Jan 24, 2014 by PMR
With the semantic web machines can autonomously carry out many knowledge-based tasks as well as humans. The main problems are not technical but the prevention of access to information. I advocate automatic downloading and indexing of all scientific information
Amanuens.is HUmans and machines annotating scholarly literature TheContentMine
Published on May 19, 2016 by PMR
about 10,000 scholarly articles ("papers") are published each day. Amanuens.is is a symbiont of ContentMine and Hypothes.is (both Shuttleworth projects/Fellows) which annotates theses using an array of controlled vocabularies ("dictionaries"). The results, in semantic form are used to annotate the original material. The talk had live demos and used plant chemistry as the examples
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Mining the scientific literature for plants and chemistrypetermurrayrust
ContentMine can read the daily scientific literature and extract facts. This talk was given to the OpenPlant project - with whom ContentMine collaborate at a meeting on 2016-07-25/27 in Norwich. Examples of extracted facts are given.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
ContentMining for France and Europe; Lessons from 2 years in UKpetermurrayrust
I have spend 2 years carrying out Content Mining (aka Text and Data Mining) in the UK under the 2014 "Hargreaves" exception. This talk was given in Paris, to ADBU , after France had passed the law of the numeric Republique. I illustrate what worked in what did not and why and offer ideas to France and Europe
El Ensayo Clínico Aleatorio: introducciónCarlos Cuello
Para cualquiera que quiera entender las razones de la distribución aleatoria y el uso de los ECAs para las revisiones sistemáticas y síntesis de la evidencia
Sesión clínica: "Meta análisis y revisiones sistemáticas"csjesusmarin
Por la Dra. Eloisa Delsors, médico de familia y tutora de residentes del Centro de Salud Jesús Marín, nos habla mediante una sesión clínica sobre los meta análisis y revisiones sistemáticas.
Carole Goble presents the Bioschemas | OSFair2017 Workshop
Workshop title: How FAIR friendly is your data catalogue?
Workshop overview:
This workshop will build upon the work planned by the EOSCpilot data interoperability task and the BlueBridge workshop held on April 3 at the RDA meeting. We will investigate common mechanisms for interoperation of data catalogues that preserve established community standards, norms and resources, while simplifying the process of being/becoming FAIR. Can we have a simple interoperability architecture based on a common set of metadata types? What are the minimum metadata requirements to expose FAIR data to EOSC services and EOSC users?
DAY 3 - PARALLEL SESSION 6 & 7
Construct a EMBASE Search that complements your MEDLINE search
Discuss other databases to consider for searching
Understand the role of GreyLit in systematic reviews
Searching for clinical trials
Download and manage results
The increasing availability of free and open access resources for scientists on the internet presents us with a revolution in data availability. The Royal Society of Chemistry hosts ChemSpider, a free access website for chemists built with the intention of building community for chemists (http://www.chemspider.com/).
ChemSpider is an aggregator of chemistry related information, at present over 20 million unique chemical entities linked out to over 300 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. It is also a public deposition platform where chemists can deposit their own data including novel structures, analytical data, synthesis procedures and host data associated with the growing activities associated with Open Notebook Science.
This presentation will examine chemistry on the internet, the dubious quality of what is available and how the ChemSpider crowdsourced curation platform is fast becoming one of the centralized hubs for resourcing information about chemical entities.
We will also review our efforts to provide free resources for synthesis procedures, spectral data and structure-based searching of the chemistry literature and how chemists can contribute directly to each of these projects.
A systematic review uses systematic and explicit methods to identify, select, critically appraise, and extract and analyze data from relevant research [Higgins & Green 2011].
A Global Commons for Scientific Data: Molecules and Wikidatapetermurrayrust
Methods for extracting facts from the scientific literature, and linking them to Wikidata IDs. Wikidata is introduced by an architectural example and bioscience. Then we explore how data can be extracted from text and from images
This was a presentation I gave to an audience at Nature Publishing Group in New York on May 7th 2009. It's a long presentation and over an hour in length. Not much new here relative to other presentations...just a knitting together of many of the others on here.
There is an increasing availability of free and open access resources for scientists to use on the internet. Coupled with an increasing number of Open Source software programs we are in the middle of a revolution in data availability and tools to manipulate these data. ChemSpider is a free access website built with the intention of providing a structure centric community for chemists. As an aggregator of chemistry related information from many sources, at present over 21.5 million unique chemical entities from over 190 separate data sources, ChemSpider has taken on the task of both robotically and manually integrating and curating publicly available data sources. ChemSpider has also provided an environment for users to deposit, curate and annotate chemistry-related information. This has allowed the community to enhance ChemSpider by adding analytical data, associating synthetic pathways and publications and connecting to social networking resources. I will discuss how ChemSpider is fast becoming the premier curated platform and centralized hub for resourcing information about chemical entities and how the platform provides the foundation data for services allowing the analysis of analytical data and collaborative science.
The internet has provided access to unprecedented quantities of data. In the domain of chemistry specifically over the past decade the web has become populated with tens of millions of chemical structures and related properties of assays together with tens of thousands of spectra and syntheses. The data have, to a large extent, remained disparate and disconnected. In recent years with the wave of Web 2.0 participation any chemist can contribute to both the sharing and validation of chemistry-related data whether it be via Wikipedia, the online encyclopedia, or one of the multiple public compound databases. The presentation will offer a perspective of what is available today, our experiences of building a public compound database to link together the internet and a suggested path forward for enabling even greater integration and connectivity for chemistry data for the masses to both use and participate in developing.
PubChem: a public chemical information resource for big data chemistrySunghwan Kim
Presented at the Joint Statistical Meetings (JSM) 2020 (virtual) on August 3, 2020.
==== Abstract ====
The idea of “big data” has recently been drawing much attention of the scientific community as well as the general public. An example of big data in Chemistry is the data contained in PubChem, which is a public database of chemical substance descriptions and their biological activities at the National Institutes of Health. PubChem is a sizeable system with 235 million depositor-provided substance descriptions, 96 million unique chemical structures, 1.1 million biological assays, and 268 million biological activity result outcomes. It also contains significant amounts of scientific research data and the inter-relationships between chemicals, proteins, genes, scientific literature, patents and more. PubChem resources have been used in many studies for developing bioactivity and toxicity prediction models, discovering multi-target ligands, and identifying new macromolecule targets of compounds (for drug-repurposing or off-target side effect prediction). This presentation provides an overview of how PubChem’s data, tools, and services can be used for bioassay data analysis and virtual screening (VS) and discusses important aspects of exploiting PubChem for drug discovery.
The Royal Society of Chemistry (RSC) is a major participant in providing access to chemistry related data via the web. As an internationally renowned society for the chemical sciences, a scientific publisher and the host of the ChemSpider database for the community, RSC continues to make dramatic strides in providing online access to data. ChemSpider provides access to over 30 million chemicals sourced from over 500 data suppliers and linked out to related information on the web. The platform is a crowdsourcing environment whereby members of the community can participate in validating and expanding the content of the database. With a set of application programming interfaces ChemSpider is used by various organizations and projects to serve up data for various purposes. These include structure identification for mass spectrometry instrument vendors, RSC databases such as the Marinlit natural products database and a European grant-based project from the Innovative Medicines Initiative fund. This presentation will provide an overview of various cheminformatics activities and projects that RSC is involved with to serve the medicinal chemistry community. This will include the Open PHACTS semantic web project, the PharmaSea project to identify new pharmaceutical leads from the ocean and the UK National Compound Collection to identify new lead compounds contained within PhD theses.
Can machines understand the scientific literature?petermurrayrust
A presentation to Cambridge MPhil Computational Biology. 2020-11-11 . Presenters Peter Murray-Rust, Shweata Hegde and Ambreen Hamadani from https://github.com/petermr/openvirus .
This chunk is PMR with a large break in the middle for SH and AH talks.
I cover Global Challenges, knowledge equity, semantics of scientific articles, Wikidata, Data Extraction from images, and ethics/politics.
Answer: Yes, technically. No, politically as the Publisher-Academic Complex will block it.
Semantic content created from Open Access papers to help in the fight against viral epidemics. Includes contributions from NIPGR interns, 5 supported by Indian National Young Academy of Scientists.
Overview of openVirus project. Interns in India have worked for 2 months to extract scientific knowledge from the literature about viral epidemics. Covers data science, machine learning and virtual collaboration
Automatic mining of data from materials science literaturepetermurrayrust
The literature on materials science (batteries, etc.) contains huge amounts of scientific facts, but not in easily accessible form. our AMI program has been developed to automatically:
scrape , clean, annotate and display/publish
data for re-use in science.
Examples will be given from electrochemistry, magnetism and other fields . The general principles and (open) tech are applicable to many other disciplines.
A presentation by Open Climate Knowledge for European Forum for Advanced Practices. Showing how the scientific literature can be searched for knowledge on this multidisciplinary topic.
XML for science; its huge potential; but are pubiishers preventing it?petermurrayrust
XML can represent almost all well derfined scientific objects. chemistry, plants medcine. But it's not yet widely used. Is this because publishers oppose thr re-use of science?
Early Career Reseachers in Science. Start Early, Be Open , Be Bravepetermurrayrust
Highlights the importance of supporting Early Career Researchers to pursue their own ideas, possibly alongside their main research. Illustrated with biology but applies to all fields of science. This was a 14 min presentation and shows narratives of how ECRs develop and reinforce each other.
Presentation given at NUI, Galway 2019-04-11 for Open Science Week.
An overview of Early Career Researchers, their innovation and contribution towards Open Infrastructure
The ContentMine system (Open Source) can search EuropePMC and download hundreds of articles in seconds. These can be indexed by AMI dictionaries allowing a rapid evaluations and refinement of the search
The scientific and medical literature is a vast resource of knowledge, but it needs turning into semantic FAIR form. The ContentMine can do this and we presented a rapid overview of the potential
A 10-minute talk to lovers of early science (e.g. 1600-1900) at the Royal Society. Archivists , computer vision, scientific historical metadata all relevant.
I chose 4 examples of monochrome diagrams that I can extract something from automatically. Some of the methids would scale to larger volumes , e.g. tables for figures, or maps with points
WikiFactMine: Ontology for Everybody and Everythingpetermurrayrust
WikiFactMine https://www.wikidata.org/wiki/Wikidata:WikiFactMine consists of several hundreds dictionaries created from Wikidata. They cover everything from science to medicine to geo to arts. Every item has a unique identifier (Q) and normally has several properties (P) creating a series of triples. Using SPARQL it's possible to create sophiticated queries and run them in seconds
The Publisher -Academic complex is a dystopian cycle where academia gives (mega)publishers manuscripts, reviews and money and the publishers give personal and institutional glory(vanity). This is analysed in its origins, impact and harm. The disruption can come from Advocacy/Activism, Community and Tools. Disruption comes from doing things Better or Novel, not Prices
AUDIO : https://soundcloud.com/damahub/peter-murray-rust-disturbing-the-publisher-academic-complex-210418-british-library
Thanks to DaMaHub
This has now been edited by Ewan McAndrew (Edinburgh Wikimedian in Residence) many thanks - to synchronize the slides with the soundtrack. https://media.ed.ac.uk/media/1_46h85ltt Brilliant
Paradise Lost and The Right to Read is the Right to Minepetermurrayrust
Presented to UIUC CIRSS seminars to a mixed group of Library, CS, domain scientists with a great contingent of Early Career Researchers. Starts by honouring the creation of the wonderful NCSA Mosaic at UIUC in 1993 and the paradise of knowledge and community it opened. Then shows the gradual and tragic decline of the web into a megacorporate neocolonialist empire, where knowledge is sacrificed for money and power.
You have seen many of the slides before but the words are different and have been recorded.
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
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
Acute scrotum is a general term referring to an emergency condition affecting the contents or the wall of the scrotum.
There are a number of conditions that present acutely, predominantly with pain and/or swelling
A careful and detailed history and examination, and in some cases, investigations allow differentiation between these diagnoses. A prompt diagnosis is essential as the patient may require urgent surgical intervention
Testicular torsion refers to twisting of the spermatic cord, causing ischaemia of the testicle.
Testicular torsion results from inadequate fixation of the testis to the tunica vaginalis producing ischemia from reduced arterial inflow and venous outflow obstruction.
The prevalence of testicular torsion in adult patients hospitalized with acute scrotal pain is approximately 25 to 50 percent
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.
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.
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.
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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.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
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.
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Cochrane workshop2016
1. Workshop overview
• Y/our backgrounds and interests and what we want
• How does mining work and what can it do for YOU/Cochrane?
• Demonstration with emphasis on dictionaries.
• What would YOU like a system to do?
• Your dictionary/ies in action
• Advanced (chemistry, diagram mining)
• ANY early adopter can obtain our (Open) software and run it at
home for any resource (medical, agricultural, government, climate,
etc.). We will help you during next 24 hours.
• All material CC BY.
2. Cochrane UK & Ireland
Symposium 2016,
Birmingham, UK, 2016-03-15
Let the Machine Help
with your
Systematic Reviews
Peter Murray-Rust1,2
Christopher Kittel2
[1]University of Cambridge
[2]TheContentMine
Simple, Universal,
Knowledge creation and re-use
3. The Right to Read is the Right to Mine**PeterMurray-Rust, 2011
http://contentmine.org
4. Resources
• Europe PubMedCentral http://europepmc.org/
• ContentMine toolkit https://github.com/ContentMine/
• Wikidata:
https://www.wikidata.org/wiki/Wikidata:Main_Page
• Hypothes.is https://hypothes.is/ [1]
• Etherpad: http://pads.cottagelabs.com/p/cochrane2016
• Note: early adopters can obtain our (Open) software and
run it at home…
• [1] Not used in CochraneBham workshop
23. Systematic Reviews
Can we:
• eliminate true negatives automatically?
• extract data from formulaic language?
• mine diagrams?
• Annotate existing sources?
• forward-reference clinical trials?
24. Polly has 20 seconds to read this paper…
…and 10,000 more
25. ContentMine software can do this in a few minutes
Polly: “there were 10,000 abstracts and due
to time pressures, we split this between 6
researchers. It took about 2-3 days of work
(working only on this) to get through
~1,600 papers each. So, at a minimum this
equates to 12 days of full-time work (and
would normally be done over several weeks
under normal time pressures).”
26. 400,000 Clinical Trials
In 10 government registries
Mapping trials => papers
http://www.trialsjournal.com/content/16/1/80
2009 => 2015. What’s
happened in last 6 years??
Search the whole scientific literature
For “2009-0100068-41”