AIMC Topic: Disease Management

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Standard operating procedure for curation and clinical interpretation of variants in cancer.

Genome medicine Nov 29, 2019
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the co...
Disease Management Practice Patterns, Physicians' Disease Susceptibility Clinical Competence Models, Theoretical Knowledge Bases Humans Neoplasms
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Machine Learning and Artificial Intelligence in Neurocritical Care: a Specialty-Wide Disruptive Transformation or a Strategy for Success.

Current neurology and neuroscience reports Nov 13, 2019
PURPOSE OF REVIEW: Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic mana...
Critical Care Disease Management Nervous System Diseases Humans Artificial Intelligence Machine Learning
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Machine learning and blood pressure.

Journal of clinical hypertension (Greenwich, Conn.) Sep 19, 2019
Machine learning (ML) is a type of artificial intelligence (AI) based on pattern recognition. There are different forms of supervised and unsupervised learning algorithms that are being used to identify and predict blood pressure (BP) and other measu...
Cardiovascular Diseases Risk Assessment Hypertension Disease Management Artificial Intelligence Humans Machine Learning Prognosis
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Artificial Intelligence Methods for Surgical Site Infection: Impacts on Detection, Monitoring, and Decision Making.

Surgical infections Aug 27, 2019
There has been tremendous growth in the amount of new surgical site infection (SSI) data generated. Key challenges exist in understanding the data for robust clinical decision-support. Limitations of traditional methodologies to handle these data le...
Epidemiological Monitoring Decision Making Surgical Wound Infection Disease Management Artificial Intelligence Image Processing, Computer-Assisted Humans
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Can Machine Learning help us in dealing with treatment resistant depression? A review.

Journal of affective disorders Aug 13, 2019
BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms relief and up to 15% of patients remain symptomatic even after multiple trials are applied, configuring a state called treatment resistant depression ...
Drug Resistance Evidence-Based Practice Depressive Disorder, Treatment-Resistant Male Disease Management Antidepressive Agents Humans Machine Learning Algorithms Female Adult
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Presidential Address: On Resisting the Narcissism of the Present.

Annals of surgical oncology Aug 1, 2019
Breast Neoplasms Disease Management Automation Humans Artificial Intelligence Female Narcissism
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Patient-based prediction algorithm of relapse after allo-HSCT for acute Leukemia and its usefulness in the decision-making process using a machine learning approach.

Cancer medicine Jul 15, 2019
Although allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for high-risk acute leukemia (AL), some patients still relapse. Since patients simultaneously have many prognostic factors, difficulties are associated with...
Models, Theoretical Treatment Outcome Decision Trees Survival Analysis Disease Management Hematopoietic Stem Cell Transplantation Prognosis Clinical Decision-Making Female Humans Machine Learning Leukemia, Myeloid, Acute Male Middle Aged Young Adult Transplantation, Homologous Algorithms Patient Participation Adult
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Artificial intelligence to support clinical decision-making processes.

EBioMedicine Jul 11, 2019
Communicable Diseases Neural Networks, Computer Disease Management Clinical Decision-Making Humans Artificial Intelligence Machine Learning Decision Support Systems, Clinical Medical Informatics
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A renaissance of teleophthalmology through artificial intelligence.

Eye (London, England) Jan 8, 2019
Ophthalmology Telemedicine Disease Management Humans Diabetic Retinopathy Female Male Artificial Intelligence Clinical Decision-Making Middle Aged
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Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods.

Journal of medical Internet research Nov 15, 2018
BACKGROUND: Measuring and predicting pain volatility (fluctuation or variability in pain scores over time) can help improve pain management. Perceptions of pain and its consequent disabling effects are often heightened under the conditions of greater...
Chronic Pain Humans Mobile Applications Volatilization Data Mining Machine Learning Disease Management
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