Obesity

Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome of Narrative Exposure Therapy vs. Dialectical Behavioral Therapy based treatment.

: A comorbidity between Borderline Personality Disorder (BPD) and Posttraumatic Stress Disorder (PTSD) is common, severely disabling, and hard to treat. The choice of an optimal psychotherapy based on patient characteristics remains challenging. This study develops models to predict the outcome of two psychotherapies for comorbid BPD and PTSD.: Data from two trials comparing Narrative Exposure The...

Association of Physical Activity from Wearable Devices and Chronic Disease Risk: Insights from the All of Us Research Program.

Physical activity is a modifiable factor influencing chronic disease risk. Previous studies often relied on self-reported activity measures or short-term assessments, limiting their accuracy. Leveraging Fitbit-derived data from the All of Us Research Program, we investigated associations between long-term physical activity patterns and chronic disease incidence in a diverse cohort. The study inclu...

EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.

In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates i...

Lifestyle modification programme for people living with HIV with metabolic dysfunction-associated steatotic liver disease: a randomised controlled trial.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major cause of chronic liver disease among people living with HIV, a...

Impact of the recent advances in coronary artery disease imaging on pilot medical certification and aviation safety: current state and future perspective.

Coronary artery disease (CAD) is highly prevalent among pilots due to the nature of their lifestyle, and occupational stresses. CAD is one the most co...

Enhancing Obstetric Decision-Making With AI: A Systematic Review of AI Models for Predicting Mode of Delivery.

Accurate prediction of the mode of delivery is critical for optimizing maternal and neonatal outcomes and reducing unnecessary cesarean sections. In r...

AI-driven personalized nutrition: RAG-based digital health solution for obesity and type 2 diabetes.

Effective management of obesity and type 2 diabetes is a major global public health challenge that requires evidence-based, scalable personalized nutr...

Innovative, Technology-Driven, Digital Tools for Managing Pediatric Urinary Incontinence: Scoping Review.

BACKGROUND: Urinary incontinence affects approximately 7% to 10% of children during the day and 9% to 12% of children during the night. Treatment main...

Artificial intelligence-based muscle analysis risk assessment of treatment-related toxicity in metastatic colorectal cancer.

IntroductionUp to 60% of adults with metastatic colorectal cancer (mCRC) receiving combination cytotoxic chemotherapy may experience loss of skeletal ...

Unraveling MASLD: The Role of Gut Microbiota, Dietary Modulation, and AI-Driven Lifestyle Interventions.

Gut microbiota has a crucial role in the pathophysiology of metabolic-associated steatotic liver disease (MASLD), influencing various metabolic mechan...

Advancement in early diagnosis of polycystic ovary syndrome: biomarker-driven innovative diagnostic sensor.

Polycystic ovary syndrome (PCOS) is a heterogeneous multifactorial endocrine disorder that affects one in five women around the globe. The pathology s...

Promoting active health with AI technologies: Current status and prospects of high-altitude therapy, simulated hypoxia, and LLM-driven lifestyle rehabilitation approaches.

In the context of the rising global prevalence of obesity, traditional intervention measures have proven insufficient to meet the demands of personali...

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.

BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular...

Retinal Ischemic Perivascular Lesions (RIPLs) as Potential Biomarkers for Systemic Vascular Diseases: A Narrative Review of the Literature.

Retinal ischemic perivascular lesions (RIPLs) are characteristic focal thinning of the inner nuclear layer, with an upward expansion of the outer nucl...

Suicide risk prediction for Korean adolescents based on machine learning.

Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, mac...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (...

Hybrid Neural network and machine learning models with improved optimization method for gut microbiome effects on the sleep quality in patients with endometriosis.

BACKGROUND AND OBJECTIVE: Endometriosis is a chronic gynecological condition known to affect the quality of life of millions of women globally, often ...

Development of intelligent robots in the wave of embodied intelligence.

On January 28, 2025, 24 humanoid robots from Unitree Ltd. performed alongside human dancers on the Spring Festival Gala of China Central Television. T...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing to morbidity, mortality and healthcare burden. Desp...

Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.

Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly among individuals over the age of 45. This conditi...