AIMC Topic: Cost-Benefit Analysis
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Economic Evaluation of Robot-Based Telemedicine Consultation Services.
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Jan 22, 2020
Through information and communication technology, telemedicine can deliver medical care without time and place restrictions, increasing health care accessibility in medically underdeveloped regions. Although there is growing interest in using robots...
Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm.
Journal of medical economics
Jan 10, 2020
As many cases of atrial fibrillation (AF) are asymptomatic, patients often remain undiagnosed until complications (e.g. stroke) manifest. Risk-prediction algorithms may help to efficiently identify people with undiagnosed AF. However, the cost-effec...
The potential of placing a digital assistant in patients' homes.
The British journal of general practice : the journal of the Royal College of General Practitioners
Dec 26, 2019
Body Composition Analysis of Computed Tomography Scans in Clinical Populations: The Role of Deep Learning.
Lifestyle genomics
Dec 10, 2019
BACKGROUND: Body composition is increasingly being recognized as an important prognostic factor for health outcomes across cancer, liver cirrhosis, and critically ill patients. Computed tomography (CT) scans, when taken as part of routine care, provi...
Humans
Neural Networks, Computer
Tomography, X-Ray Computed
Lumbar Vertebrae
Cost-Benefit Analysis
Pattern Recognition, Automated
Lumbosacral Region
Body Mass Index
Subcutaneous Fat
Muscle, Skeletal
Adipose Tissue
Body Composition
Reproducibility of Results
Deep Learning
Image Processing, Computer-Assisted
ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial.
American heart journal
Oct 25, 2019
BACKGROUND: A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automaticall...
The benefits of and barriers to using a social robot PARO in care settings: a scoping review.
BMC geriatrics
Aug 23, 2019
BACKGROUND: Given the complexity of providing dementia care in hospitals, integrating technology into practice is a high challenge and an important opportunity. Although there are a growing demand and interest in using social robots in a variety of c...
Increase Trichomonas vaginalis detection based on urine routine analysis through a machine learning approach.
Scientific reports
Aug 19, 2019
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a machine learning (ML)-based strategy to increase the detection rate of T. vaginalis in urine. On the bas...
Towards the automated economic assessment of newborn screening for rare diseases.
Journal of biomedical informatics
May 22, 2019
OBJECTIVE: Economic assessments of newborn screening programs for rare diseases involve the use of models and require huge efforts to synthesize information from different sources. Sharing and automatically or semi-automatically reusing this informat...
Broadening the Perspective of Cost-Effectiveness Modeling in Chronic Obstructive Pulmonary Disease: A New Patient-Level Simulation Model Suitable to Evaluate Stratified Medicine.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Dec 20, 2018
OBJECTIVES: To develop a health economic model that included a great diversity of patient characteristics and outcomes for chronic obstructive pulmonary disease (COPD), which can be used to inform decisions about stratified medicine in COPD.
Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.
BMC geriatrics
Oct 3, 2018
BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a ne...
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