Cardiovascular

Prevention

Latest AI and machine learning research in prevention for healthcare professionals.

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Robotically assisted treadmill exercise training for improving peak fitness in chronic motor incomplete spinal cord injury: A randomized controlled trial.

OBJECTIVE: To assess the effectiveness of robotically assisted body weight supported treadmill training (RABWSTT) for improving cardiovascular fitness in chronic motor incomplete spinal cord injury (CMISCI).

Dec 18 2014 25520035

A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke.

Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducing activity-dependent brain plasticity. The purpose of this study was to investigate the efficacy of an EEG-based MI BCI system coupled with MIT-Manus shoulder-elbow robotic feedback (BCI-Manus) for subjects with chronic stroke with upper-limb hemipar...

Apr 21 2014 24756025
Work-rate-guided exercise testing in patients with incomplete spinal cord injury using a robotics-assisted tilt-table.

PURPOSE: Robotics-assisted tilt-table (RTT) technology allows neurological rehabilitation therapy to be started early thus alleviating some secondary ...

Apr 8 2014 24712412
Functional outcomes after TORS for oropharyngeal cancer: a systematic review.

Summarize functional outcomes after transoral robotic surgery (TORS) ± adjuvant therapy for oropharyngeal cancer (OPC). A systematic review was conduc...

Mar 19 2014 24643851
Effect of initiating an ARB- versus ACEI-based regimen on dementia risk, a target trial emulation of 2.5 million US Veterans

Background: Hypertension is a modifiable risk factor for dementia, yet the comparative effectiveness of angiotensin receptor blockers (ARBs) versus an...

Machine Learning for Depression Screening and Intervention: an Original Circadian Rhythm Score-based Methodology

Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of inte...

Jul 6 2026 2607.04648v1
Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data

Counterfactual explanations (CEs) for multivariate time-series classifiers are often difficult to interpret in domains where experts reason in terms o...

Jul 2 2026 2607.01838v1
Nutrient-dependent hippocampus dopamine signaling enhances meal-related episodic memory and reduces food intake

Background: Dopamine (DA) is a neurotransmitter critically involved in food-related reinforcement learning. While mesolimbic DA reward-associated sign...

A Point Cloud Transformer for Remote Monitoring and Automated Assessment of Physical Rehabilitation Exercises

Rehabilitation exercises are essential in restoring lost physical functions of patients suffering from various diseases (e.g., Parkinson's, back pain)...

Jun 29 2026 2606.30309v1
Response consistency of ChatGPT-4o for Type 2 Diabetes Nutrition and Physical-activity Recommendations: A Pilot NLP-based Assessment of GPT outputs

Generative AI tools such as ChatGPT are increasingly used by the public to seek guidance on diet and physical activity for type 2 diabetes (T2D) preve...

Silent Manipulation of Mental Health Treatment Recommendations from a Large Language Model

Importance. Large language models (LLMs) increasingly inform mental health decisions by patients and clinicians. Inference-time activation steering ca...

Nickel and Dimed: How a Common Earth Element is Short-Changing Our Health

Nickel has been studied for a long time as an environmental contaminant but less so in its connection to population health. It does not announce itsel...

Heterogeneity of Treatment Effect of Aspirin and Clinically Significant Bleeding in Older Adults

Aim: The global population of older adults is growing, and older age is linked to higher bleeding risk. Although guidelines discourage aspirin for pri...

Calibrating trust in AI-assisted pituitary surgery

Background: Endoscopic endonasal transsphenoidal surgery (EETS) requires navigation around neurocritical anatomy. Today, artificial intelligence clini...

An LSEC-focused computational drug repurposing platform for liver fibrosis: Identification of vorinostat and other LSEC-protective candidates

Liver sinusoidal endothelial cells (LSECs) are increasingly recognized as a critical yet underexplored cell type in anti-fibrotic drug development. Th...

Professionalism Pulse: Development and Validation of a Natural Language Processing Pipeline and Dashboard for Safety Culture Surveillance in NYC Health + Hospitals

Background: Professionalism and effective communication are foundational determinants of patient safety and quality of care. Unprofessional behaviors ...

Real-time hip biomechanics from smart garments via a physics-informed neural network

Tissue-level mechanical stimuli are primary drivers of tissue adaptation and can be optimised during conservative treatments to improve treatment outc...

Estimation of Physiological Metrics from Resting ECGs Using Deep Learning in the UK Biobank, Including submaximal exercise derived VO2max, Body Fat Percentage, and Grip Strength

Maximal oxygen consumption VO2max is the gold standard for cardiorespiratory fitness but requires resource-intensive physical testing. Recent reports ...

CT Attenuation Map Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation

Aim: Exercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be us...

Use of Large Language Models by U.S. Adults to Support Exercise: A Survey Study

Background: Large Language Model (LLM) chatbots are increasingly used for exercise and fitness topics, yet users' experience with these tools remains ...

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