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https://www.readbyqxmd.com/read/29507784/artificial-intelligence-in-healthcare-past-present-and-future
#1
REVIEW
Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, Yongjun Wang
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data...
December 2017: Stroke and Vascular Neurology
https://www.readbyqxmd.com/read/29393869/using-twitter-to-better-understand-the-spatiotemporal-patterns-of-public-sentiment-a-case-study-in-massachusetts-usa
#2
Xiaodong Cao, Piers MacNaughton, Zhengyi Deng, Jie Yin, Xi Zhang, Joseph G Allen
Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale...
February 2, 2018: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/29336344/-the-urologist-of-the-future-and-new-technologies
#3
Francois Peinado, Atanasio Fernández, Fernando Teba, Guillermo Celada, Marco Antonio Acosta
The last 25 years have brought about revolutionary changes for medicine and in particular for urology: internet was only in its infancy, medical records were written on paper, searches for medical information were done in the hospital library, medical articles were photocopied and our relationship with patients only existed face to face. Social networks had not yet appeared and even Google did not exist. Just imagine what might happen during the next 25 years, we're going to see even more radical changes. The urologist of the future is going to see the arrival of artificial intelligence, collaborative medicine, telemedicine, machine learning, the Internet of Things and personalized robotics; in the meantime, social media will continue to transform the interaction between physician and patient...
January 2018: Archivos Españoles de Urología
https://www.readbyqxmd.com/read/29134320/artificial-intelligence-in-neurodegenerative-disease-research-use-of-ibm-watson-to-identify-additional-rna-binding-proteins-altered-in-amyotrophic-lateral-sclerosis
#4
Nadine Bakkar, Tina Kovalik, Ileana Lorenzini, Scott Spangler, Alix Lacoste, Kyle Sponaugle, Philip Ferrante, Elenee Argentinis, Rita Sattler, Robert Bowser
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with no effective treatments. Numerous RNA-binding proteins (RBPs) have been shown to be altered in ALS, with mutations in 11 RBPs causing familial forms of the disease, and 6 more RBPs showing abnormal expression/distribution in ALS albeit without any known mutations. RBP dysregulation is widely accepted as a contributing factor in ALS pathobiology. There are at least 1542 RBPs in the human genome; therefore, other unidentified RBPs may also be linked to the pathogenesis of ALS...
February 2018: Acta Neuropathologica
https://www.readbyqxmd.com/read/28991752/linear-time-algorithms-to-construct-populations-fitting-multiple-constraint-distributions-at-genomic-scales
#5
Enrico Siragusa, Niina Haiminen, Filippo Utro, Laxmi Parida
Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions...
October 9, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28978832/clinical-sequencing-in-leukemia-with-the-assistance-of-artificial-intelligence
#6
Arinobu Tojo
Next generation sequencing (NGS) of cancer genomes is now becoming a prerequisite for accurate diagnosis and proper treatment in clinical oncology. Because the genomic regions for NGS expand from a certain set of genes to the whole exome or whole genome, the resulting sequence data becomes incredibly enormous and makes it quite laborious to translate the genomic data into medicine, so-called annotation and curation. We organized a clinical sequencing team and established a bidirectional (bed-to-bench and bench-to-bed) system to integrate clinical and genomic data for hematological malignancies...
2017: [Rinshō Ketsueki] the Japanese Journal of Clinical Hematology
https://www.readbyqxmd.com/read/28924815/automatic-determination-of-the-need-for-intravenous-contrast-in-musculoskeletal-mri-examinations-using-ibm-watson-s-natural-language-processing-algorithm
#7
Hari Trivedi, Joseph Mesterhazy, Benjamin Laguna, Thienkhai Vu, Jae Ho Sohn
Magnetic resonance imaging (MRI) protocoling can be time- and resource-intensive, and protocols can often be suboptimal dependent upon the expertise or preferences of the protocoling radiologist. Providing a best-practice recommendation for an MRI protocol has the potential to improve efficiency and decrease the likelihood of a suboptimal or erroneous study. The goal of this study was to develop and validate a machine learning-based natural language classifier that can automatically assign the use of intravenous contrast for musculoskeletal MRI protocols based upon the free-text clinical indication of the study, thereby improving efficiency of the protocoling radiologist and potentially decreasing errors...
April 2018: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28740869/comparing-sequencing-assays-and-human-machine-analyses-in-actionable-genomics-for-glioblastoma
#8
Kazimierz O Wrzeszczynski, Mayu O Frank, Takahiko Koyama, Kahn Rhrissorrakrai, Nicolas Robine, Filippo Utro, Anne-Katrin Emde, Bo-Juen Chen, Kanika Arora, Minita Shah, Vladimir Vacic, Raquel Norel, Erhan Bilal, Ewa A Bergmann, Julia L Moore Vogel, Jeffrey N Bruce, Andrew B Lassman, Peter Canoll, Christian Grommes, Steve Harvey, Laxmi Parida, Vanessa V Michelini, Michael C Zody, Vaidehi Jobanputra, Ajay K Royyuru, Robert B Darnell
OBJECTIVE: To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. METHODS: Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs...
August 2017: Neurology. Genetics
https://www.readbyqxmd.com/read/28562310/mental-health-services-utilization-and-expenditures-among-children-enrolled-in-employer-sponsored-health-plans
#9
Angela Wangari Walter, Yiyang Yuan, Howard J Cabral
BACKGROUND AND OBJECTIVES: Mental illness in children increases the risk of developing mental health disorders in adulthood, and reduces physical and emotional well-being across the life course. The Mental Health Parity and Addiction Equity Act (MHPAEA, 2008) aimed to improve access to mental health treatment by requiring employer-sponsored health plans to include insurance coverage for behavioral health services. METHODS: Investigators used IBM Watson/Truven Analytics MarketScan claims data (2007-2013) to examine: (1) the distribution of mental illness; (2) trends in utilization and out-of-pocket expenditures; and (3) the overall effect of the MHPAEA on mental health services utilization and out-of-pocket expenditures among privately-insured children aged 3 to 17 with mental health disorders...
May 2017: Pediatrics
https://www.readbyqxmd.com/read/28534755/cognitive-computing-and-the-future-of-health-care-cognitive-computing-and-the-future-of-healthcare-the-cognitive-power-of-ibm-watson-has-the-potential-to-transform-global-personalized-medicine
#10
Mohamed Nooman Ahmed, Andeep S Toor, Kelsey O'Neil, Dawson Friedland
Welcome to the era of cognitive health care, a new partnership between human beings and technology with the goal of transforming health care on a global scale.
May 2017: IEEE Pulse
https://www.readbyqxmd.com/read/28508821/measuring-the-negative-impact-of-long-sitting-hours-at-high-school-students-using-the-microsoft-kinect
#11
Norbert Gal-Nadasan, Emanuela Georgiana Gal-Nadasan, Vasile Stoicu-Tivadar, Dan V Poenaru, Diana Popa-Andrei
This paper suggests the usage of the Microsoft Kinect to detect the onset of the scoliosis at high school students due to incorrect sitting positions. The measurement is done by measuring the overall posture in orthostatic position using the Microsoft Kinect. During the measuring process several key points of the human body are tracked like the hips and shoulders to form the postural data. The test was done on 30 high school students who spend 6 to 7 hours per day in the school benches. The postural data is statistically processed by IBM Watson's Analytics...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28423974/competitive-bass-anglers-a-new-concern-in-sports-medicine
#12
Connor R Read, Shawna L Watson, Jorge L Perez, A Reed Estes
OBJECTIVE: Competitive bass angling involves sport fishing against other anglers while targeting a species of fish known as the black basses. Due to the rapidly growing popularity of high school competitive bass angling in Alabama and the nature of the casting motion similar to that of overhead athletes, we sought to examine the prevalence of sports type injuries in this population. METHODS: In spring 2016, an anonymous survey was distributed across two large scale competitive high school fishing tournaments, allowing for a broad sampling of anglers throughout the state of Alabama...
April 28, 2017: Physician and Sportsmedicine
https://www.readbyqxmd.com/read/27977903/elementary-my-dear-watson-the-era-of-natural-language-processing-in-transplantation
#13
EDITORIAL
B Ho, A Skaro, S Montag, L Zhao
No abstract text is available yet for this article.
December 15, 2016: American Journal of Transplantation
https://www.readbyqxmd.com/read/27864232/bringing-precision-medicine-to-community-oncologists
#14
(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.
January 2017: Cancer Discovery
https://www.readbyqxmd.com/read/27729304/ibm-watson-analytics-automating-visualization-descriptive-and-predictive-statistics
#15
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
#16
COMPARATIVE STUDY
Alberto M Marchevsky, Ann E Walts, Mark R Wick
Evidence-based pathology 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. Evidence-based pathology 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...
March 2017: Human Pathology
https://www.readbyqxmd.com/read/27395043/the-critical-domain-size-of-stochastic-population-models
#17
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...
February 2017: 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
#18
REVIEW
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
#19
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
#20
EDITORIAL
Richard I Shader
No abstract text is available yet for this article.
January 1, 2016: Clinical Therapeutics
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