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Faster and better than a physician?: Assessing diagnostic proficiency of ChatGPT in misdiagnosed individuals with neuromyelitis optica spectrum disorder.

Journal of the neurological sciences
BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a commonly misdiagnosed condition. Driven by cost-consciousness and technological fluency, distinct generations may gravitate towards healthcare alternatives, including artificial intellig...

Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.

Journal of the neurological sciences
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasiv...

Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.

Diabetes research and clinical practice
AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to ass...

Diagnostic Accuracy of Artificial Intelligence-Based Chest X-Ray reading for screening of Tuberculosis.

Journal of Nepal Health Research Council
BACKGROUND: Tuberculosis remains a public health challenge in Nepal and ranks as the seventh leading cause of death in the country. The END Tuberculosis strategy stresses - the screening for symptoms alone may not suffice; additional screening tools ...

Machine Learning and Statistical Analyses of Sensor Data Reveal Variability Between Repeated Trials in Parkinson's Disease Mobility Assessments.

Sensors (Basel, Switzerland)
Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability o...

A Machine Learning Classification Model for Gastrointestinal Health in Cancer Survivors: Roles of Telomere Length and Social Determinants of Health.

International journal of environmental research and public health
BACKGROUND: Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is crucial for preventing and managing this distress. ...

Machine learning analysis of sex and menopausal differences in the gut microbiome in the HELIUS study.

NPJ biofilms and microbiomes
Sex differences in the gut microbiome have been examined previously, but results are inconsistent, often due to small sample sizes. We investigated sex and menopausal differences in the gut microbiome in a large multi-ethnic population cohort study, ...

A modular machine learning tool for holistic and fine-grained behavioral analysis.

Behavior research methods
Artificial intelligence techniques offer promising avenues for exploring human body features from videos, yet no freely accessible tool has reliably provided holistic and fine-grained behavioral analyses to date. To address this, we developed a machi...

Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-Assisted Gait Rehabilitation (RAGR) is an established clinical practice to encourage neuroplasticity in patients with neuromotor disorders. Nevertheless, tasks repetition imposed by robots may induce boredom, affecting clinical outc...