Latest AI and machine learning research in surveys for healthcare professionals.
Our long-term goal is to enable a robot to engage in partner dance for use in rehabilitation therapy, assessment, diagnosis, and scientific investigations of two-person whole-body motor coordination. Partner dance has been shown to improve balance and gait in people with Parkinson's disease and in older adults, which motivates our work. During partner dance, dance couples rely heavily on haptic in...
BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographic, clinical questionnaire, environmental, neuropsychological, neuroimaging, and genetic information can predict therapeutic response following methylp...
For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable disea...
A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like En...
The use of robots in therapy for children with autism spectrum disorder (ASD) raises issues concerning the ethical and social acceptability of this te...
Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a subs...
Outcomes from 5 years of treatment with agalsidase alfa enzyme replacement therapy (ERT) for Fabry disease in patients enrolled in the Fabry Outcome S...
Expert opinion plays an important role when choosing clusters of chemical compounds for further investigation. Often, the process by which the cluster...
Computerizing paper-based CPG and then executing them can provide evidence-informed decision support to physicians at the point of care. Semantic web ...
The consistency of propensity score (PS) estimators relies on correct specification of the PS model. The PS is frequently estimated using main-effects...
This paper studies the stability and Hopf bifurcation in a class of high-dimension neural network involving the discrete and distributed delays under ...
BACKGROUND: Validated training exercises are essential tools for surgeons as they develop technical skills to use robot-assisted minimally invasive su...
PURPOSE: Fuzzy set theory (FST) can improve various aspects of measurement with questionnaires. However, very little is known about how to use FST to ...
Carotid intima-media thickness (C-IMT) measurements provide a non-invasive assessment of subclinical atherosclerosis. The aim of the study was to asse...
Single-cell foundation models are increasingly adopted for downstream applications such as cell-type prediction. However, these predictions are often ...
Objective: Published P300-speller fusion schemes fix prior trust regardless of trial reliability; we tested whether a reliability estimate improves on...
Semi-supervised learning has shown great potential for reducing annotation costs in medical image segmentation. However, most existing methods mainly ...
Vision-language models (VLMs) are increasingly used to make decisions from visual inputs. We introduce FAIRLENS, a benchmark and evaluation framework ...
Vision-language models are increasingly used to measure urban change from repeated street-level imagery, but their longitudinal reliability is not wel...
Large Vision-Language Models produce fluent image descriptions but offer limited semantic control: users cannot reliably specify whether captions shou...