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https://www.readbyqxmd.com/read/27864232/bringing-precision-medicine-to-community-oncologists
#1
(no author information available yet)
Quest Diagnostics has teamed up with Memorial Sloan Kettering Cancer Center and IBM Watson Health to offer IBM Watson Genomics to its network of community cancer centers and hospitals. This new service aims to advance precision medicine by combining genomic tumor sequencing with the power of cognitive computing.
November 18, 2016: Cancer Discovery
https://www.readbyqxmd.com/read/27729304/ibm-watson-analytics-automating-visualization-descriptive-and-predictive-statistics
#2
Robert Eugene Hoyt, Dallas Snider, Carla Thompson, Sarita Mantravadi
BACKGROUND: We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS)...
October 11, 2016: JMIR Public Health and Surveillance
https://www.readbyqxmd.com/read/27663085/evidence-based-pathology-in-its-second-decade-toward-probabilistic-cognitive-computing
#3
Alberto M Marchevsky, Ann E Walts, Mark R Wick
Evidence-based pathology (EBP) advocates using a combination of best available data ("evidence") from the literature and personal experience for the diagnosis, estimation of prognosis and assessment of other variables that impact individual patient care. EBP relies on systematic reviews of the literature, evaluation of the quality of evidence as categorized by evidence levels and statistical tools such as meta-analyses, estimates of probabilities and odds, and others. However, it is well known that previously "statistically significant" information usually does not accurately forecast the future for individual patients...
September 20, 2016: Human Pathology
https://www.readbyqxmd.com/read/27395043/the-critical-domain-size-of-stochastic-population-models
#4
Jody R Reimer, Michael B Bonsall, Philip K Maini
Identifying the critical domain size necessary for a population to persist is an important question in ecology. Both demographic and environmental stochasticity impact a population's ability to persist. Here we explore ways of including this variability. We study populations with distinct dispersal and sedentary stages, which have traditionally been modelled using a deterministic integrodifference equation (IDE) framework. Individual-based models (IBMs) are the most intuitive stochastic analogues to IDEs but yield few analytic insights...
July 9, 2016: Journal of Mathematical Biology
https://www.readbyqxmd.com/read/27310474/how-healthcare-can-refocus-on-its-super-customers-patients-n%C3%A2-1-and-customers-doctors-and-nurses-by-leveraging-lessons-from-amazon-uber-and-watson
#5
Evelyne Kolker, Vural Özdemir, Eugene Kolker
Healthcare is transforming with data-intensive omics technologies and Big Data. The "revolution" has already happened in technology, but the bottlenecks have shifted to the social domain: Who can be empowered by Big Data? Who are the users and customers? In this review and innovation field analysis, we introduce the idea of a "super-customer" versus "customer" and relate both to 21st century healthcare. A "super-customer" in healthcare is the patient, sample size of n = 1, while "customers" are the providers of healthcare (e...
June 2016: Omics: a Journal of Integrative Biology
https://www.readbyqxmd.com/read/27130797/ibm-watson-how-cognitive-computing-can-be-applied-to-big-data-challenges-in-life-sciences-research
#6
REVIEW
Ying Chen, J D Elenee Argentinis, Griff Weber
Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed. The challenge lies in harnessing volumes of data, integrating the data from hundreds of sources, and understanding their various formats. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets...
April 2016: Clinical Therapeutics
https://www.readbyqxmd.com/read/26773356/some-reflections-on-ibm-watson-and-on-women-s-health
#7
EDITORIAL
Richard I Shader
No abstract text is available yet for this article.
January 1, 2016: Clinical Therapeutics
https://www.readbyqxmd.com/read/26677185/systems-medicine-in-oncology-signaling-network-modeling-and-new-generation-decision-support-systems
#8
REVIEW
Silvio Parodi, Giuseppe Riccardi, Nicoletta Castagnino, Lorenzo Tortolina, Massimo Maffei, Gabriele Zoppoli, Alessio Nencioni, Alberto Ballestrero, Franco Patrone
Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive...
2016: Methods in Molecular Biology
https://www.readbyqxmd.com/read/26442199/rare-disease-diagnosis-a-review-of-web-search-social-media-and-large-scale-data-mining-approaches
#9
REVIEW
Dan Svenstrup, Henrik L Jørgensen, Ole Winther
Physicians and the general public are increasingly using web-based tools to find answers to medical questions. The field of rare diseases is especially challenging and important as shown by the long delay and many mistakes associated with diagnoses. In this paper we review recent initiatives on the use of web search, social media and data mining in data repositories for medical diagnosis. We compare the retrieval accuracy on 56 rare disease cases with known diagnosis for the web search tools google.com, pubmed...
2015: Rare Diseases
https://www.readbyqxmd.com/read/26080837/oncologists-partner-with-watson-on-genomics
#10
(no author information available yet)
A new collaboration between IBM Watson Health and more than a dozen cancer centers uses the power of cognitive computing to dramatically reduce the time it takes to analyze data from patients' DNA and identify targeted treatment options.
August 2015: Cancer Discovery
https://www.readbyqxmd.com/read/26035012/biobank-classification-in-an-australian-setting
#11
Amanda Rush, Jeffrey H Christiansen, Jake P Farrell, Susan M Goode, Rodney J Scott, Kevin J Spring, Jennifer A Byrne
In 2011, Watson and Barnes proposed a schema for classifying biobanks into 3 groups (mono-, oligo-, and poly-user), primarily based upon biospecimen access policies. We used results from a recent comprehensive survey of cancer biobanks in New South Wales, Australia to assess the applicability of this biobank classification schema in an Australian setting. Cancer biobanks were identified using publically available data, and by consulting with research managers. A comprehensive survey was developed and administered through a face-to-face setting...
June 2015: Biopreservation and Biobanking
https://www.readbyqxmd.com/read/25689646/watson-will-see-you-now-a-supercomputer-to-help-clinicians-make-informed-treatment-decisions
#12
Susan Doyle-Lindrud
IBM has collaborated with several cancer care providers to develop and train the IBM supercomputer Watson to help clinicians make informed treatment decisions. When a patient is seen in clinic, the oncologist can input all of the clinical information into the computer system. Watson will then review all of the data and recommend treatment options based on the latest evidence and guidelines. Once the oncologist makes the treatment decision, this information can be sent directly to the insurance company for approval...
February 2015: Clinical Journal of Oncology Nursing
https://www.readbyqxmd.com/read/25574621/ibm-s-watson-group-signs-up-genomics-partners
#13
Mark Ratner
No abstract text is available yet for this article.
January 2015: Nature Biotechnology
https://www.readbyqxmd.com/read/25509611/watson-watson-come-here-i-want-you-johnson-johnson-s-ceo-enlists-ibm-s-big-data-service-to-find-new-drugs
#14
Mehboob Jeelani
No abstract text is available yet for this article.
October 27, 2014: Fortune
https://www.readbyqxmd.com/read/24938035/paging-dr-watson-ibm-s-watson-supercomputer-now-being-used-in-healthcare
#15
Howard Lee
No abstract text is available yet for this article.
May 2014: Journal of AHIMA
https://www.readbyqxmd.com/read/24338557/artificial-intelligence-in-medicine-and-cardiac-imaging-harnessing-big-data-and-advanced-computing-to-provide-personalized-medical-diagnosis-and-treatment
#16
REVIEW
Steven E Dilsizian, Eliot L Siegel
Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting "alert fatigue" and increased expectations for rapid and accurate diagnosis and treatment...
January 2014: Current Cardiology Reports
https://www.readbyqxmd.com/read/22942533/what-would-it-be-like-to-be-ibm-s-computer-watson
#17
Henry D Schlinger
No abstract text is available yet for this article.
2012: Behavior Analyst
https://www.readbyqxmd.com/read/22942530/making-ibm-s-computer-watson-human
#18
Howard Rachlin
This essay uses the recent victory of an IBM computer (Watson) in the TV game, Jeopardy, to speculate on the abilities Watson would need, in addition to those it has, to be human. The essay's basic premise is that to be human is to behave as humans behave and to function in society as humans function. Alternatives to this premise are considered and rejected. The viewpoint of the essay is that of teleological behaviorism. Mental states are defined as temporally extended patterns of overt behavior. From this viewpoint (although Watson does not currently have them), essential human attributes such as consciousness, the ability to love, to feel pain, to sense, to perceive, and to imagine may all be possessed by a computer...
2012: Behavior Analyst
https://www.readbyqxmd.com/read/22195076/the-sharpn-project-on-secondary-use-of-electronic-medical-record-data-progress-plans-and-possibilities
#19
Christopher G Chute, Jyotishman Pathak, Guergana K Savova, Kent R Bailey, Marshall I Schor, Lacey A Hart, Calvin E Beebe, Stanley M Huff
SHARPn is a collaboration among 16 academic and industry partners committed to the production and distribution of high-quality software artifacts that support the secondary use of EMR data. Areas of emphasis are data normalization, natural language processing, high-throughput phenotyping, and data quality metrics. Our work avails the industrial scalability afforded by the Unstructured Information Management Architecture (UIMA) from IBM Watson Research labs, the same framework which underpins the Watson Jeopardy demonstration...
2011: AMIA ... Annual Symposium Proceedings
https://www.readbyqxmd.com/read/21846786/natural-language-processing-an-introduction
#20
REVIEW
Prakash M Nadkarni, Lucila Ohno-Machado, Wendy W Chapman
OBJECTIVES: To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. TARGET AUDIENCE: This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art. SCOPE: We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture...
September 2011: Journal of the American Medical Informatics Association: JAMIA
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