Primary Care

Empagliflozin and Rapid Kidney Function Decline Incidence in Type 2 Diabetes: An Exploratory Analysis From the EMPA-REG OUTCOME Trial.

RATIONALE & OBJECTIVE: Kidney function progressively declines in most patients with type 2 diabetes (T2DM). Many develop progressive chronic kidney disease (CKD), but some experience a more rapid decline, with a greater risk of kidney failure and cardiovascular disease. In EMPA-REG OUTCOME, empagliflozin was associated with slower kidney disease progression. This post hoc analysis evaluated the ef...

Co-existence of Type 1 Diabetes Mellitus and Myasthenia Gravis: A Case Report and Review of the Literature.

BACKGROUND/OBJECTIVE: Type 1 diabetes (T1D) and myasthenia gravis (MG) are autoimmune conditions that rarely co-occur. Here, we report a child with MG who subsequently developed T1D.

How do nurses work in chronic management in the age of artificial intelligence? development and future prospects.

AI is undeniably revolutionizing medical research and patient care across diverse fields. Chronic disease nursing care, a pivotal aspect of clinical m...

A Woman With -Associated Monogenic Diabetes Treated Successfully With Repaglinide Monotherapy.

BACKGROUND/OBJECTIVE: Monogenic diabetes is a rare type of diabetes that is commonly misdiagnosed as type 1 or 2 diabetes mellitus, which adversely im...

Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations.

The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are availa...

Deep learning algorithm for predicting preterm birth in the case of threatened preterm labor admissions using transvaginal ultrasound.

PURPOSE: Preterm birth presents a major challenge in perinatal care, and predicting preterm birth remains a major challenge. If preterm birth cases ca...

Exploring the progress of artificial intelligence in managing type 2 diabetes mellitus: a comprehensive review of present innovations and anticipated challenges ahead.

A significant worldwide health issue, Type 2 Diabetes Mellitus (T2DM) calls for creative solutions. This in-depth review examines the growing severity...

Automating General Movements Assessment with quantitative deep learning to facilitate early screening of cerebral palsy.

The Prechtl General Movements Assessment (GMA) is increasingly recognized for its role in evaluating the integrity of the developing nervous system an...

Artificial Intelligence for Multiple Sclerosis Management Using Retinal Images: Pearl, Peaks, and Pitfalls.

Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory processes, demyelination, neurodegeneration, and axonal damage w...

A single session of strength training changed plasma levels of resistin, but not leptin in overweight and obese men.

Obesity has a complex multifactorial etiology and is characterized by excessive accumulation of adipose tissue. Visceral adipose tissue has deleteriou...

Benchmarking Transformer-Based Models for Identifying Social Determinants of Health in Clinical Notes.

Electronic health records (EHR) have been widely used in building machine learning models for health outcomes prediction. However, many EHR-based mode...

Multiple generation distinct toxicant exposures induce epigenetic transgenerational inheritance of enhanced pathology and obesity.

Three successive multiple generations of rats were exposed to different toxicants and then bred to the transgenerational F5 generation to assess the i...

European validation of an image-derived AI-based short-term risk model for individualized breast cancer screening-a nested case-control study.

BACKGROUND: Image-derived artificial intelligence (AI)-based risk models for breast cancer have shown high discriminatory performances compared with c...

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including o...

Machine learning techniques to predict the risk of developing diabetic nephropathy: a literature review.

PURPOSE: Diabetes is a major public health challenge with widespread prevalence, often leading to complications such as Diabetic Nephropathy (DN)-a ch...

Machine Learning and Deep Learning Techniques Applied to Diabetes Research: A Bibliometric Analysis.

BACKGROUND: The use of machine learning and deep learning techniques in the research on diabetes has garnered attention in recent times. Nonetheless, ...

Evaluation of deep learning-based depression detection using medical claims data.

Human accuracy in diagnosing psychiatric disorders is still low. Even though digitizing health care leads to more and more data, the successful adopti...

EUS coil and glue for gastric varices-prevent, treat and rescue, one therapy to rule them all?

BACKGROUND AND OBJECTIVES: In portal hypertension, gastric varix-associated bleeding is known to have higher transfusion requirements, uncontrolled bl...

A Smart Sensing Technologies-Based Intelligent Healthcare System for Diabetes Patients.

An Artificial Intelligence (AI)-enabled human-centered smart healthcare monitoring system can be useful in life saving, specifically for diabetes pati...

Machine learning approach reveals microbiome, metabolome, and lipidome profiles in type 1 diabetes.

INTRODUCTION: Type 1 diabetes (T1D) is a complex disorder influenced by genetic and environmental factors. The gut microbiome, the serum metabolome, a...