AIMC Topic: Symptom Assessment
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Artificial neural networks for simultaneously predicting the risk of multiple co-occurring symptoms among patients with cancer.
Cancer medicine
Dec 22, 2020
Patients with cancer often exhibit multiple co-occurring symptoms which can impact the type of treatment received, recovery, and long-term health. We aim to simultaneously predict the risk of three symptoms: severe pain, moderate-severe depression, a...
Utilizing an Artificial Neural Network to Predict Self-Management in Patients With Chronic Obstructive Pulmonary Disease: An Exploratory Analysis.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Dec 21, 2020
PURPOSE: The main objective of this study was to utilize an artificial neural network in an exploratory fashion to predict self-management behaviors based on reported symptoms in a sample of stable patients with chronic obstructive pulmonary disease ...
Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development.
Journal of medical Internet research
Dec 16, 2020
BACKGROUND: Assigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.
The Emerging Role of Artificial Intelligence in the Fight Against COVID-19.
European urology
Sep 17, 2020
The coronavirus disease 2019 (COVID-19) pandemic has generated large volumes of clinical data that can be an invaluable resource towards answering a number of important questions for this and future pandemics. Artificial intelligence can have an impo...
Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning.
Scientific reports
May 15, 2020
After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthrit...
Rare diseases 2030: how augmented AI will support diagnosis and treatment of rare diseases in the future.
Annals of the rheumatic diseases
Mar 24, 2020
Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.
Scientific reports
Mar 18, 2020
Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). ...
Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine.
Infection control and hospital epidemiology
Mar 3, 2020
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone-based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.
Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model.
Scientific reports
Nov 11, 2019
The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered...
Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.
Journal of affective disorders
Sep 4, 2019
BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general hospitals in China leads to possible misdiagnosis. Looking at the symptomatology of first-visit patients with MDD in different mental health services...
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