Primary Care

Obesity

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

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Is obesity a contraindication for kidney donation?

INTRODUCTION: To enlarge the donor pool, kidney donors with obesity have been considered. We hypothe...

Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is rou...

Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.

UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA ...

Recognizing Human Daily Activity Using Social Media Sensors and Deep Learning.

The human daily activity category represents individual lifestyle and pattern, such as sports and sh...

Prediction of complication related death after radical cystectomy for bladder cancer with machine learning methodology.

To create a pre-operatively usable tool to identify patients at high risk of early death (within 90...

Machine learning and blood pressure.

Machine learning (ML) is a type of artificial intelligence (AI) based on pattern recognition. There ...

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment.

Background Nonalcoholic fatty liver disease and its consequences are a growing public health concern...

Prediction and Experimental Confirmation of Novel Peripheral Cannabinoid-1 Receptor Antagonists.

Small molecules targeting peripheral CB1 receptors have therapeutic potential in a variety of disord...

Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.

Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physic...

Strategies to Tackle the Global Burden of Diabetic Retinopathy: From Epidemiology to Artificial Intelligence.

Diabetes is a global public health disease projected to affect 642 million adults by 2040, with abou...

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.

INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly re...

Construct validation of machine learning in the prediction of short-term postoperative complications following total shoulder arthroplasty.

BACKGROUND: We aimed to demonstrate that supervised machine learning (ML) models can better predict ...

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.

Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offe...

Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System.

According to the survey on various health centres, smart log-based multi access physical monitoring ...

HyperFoods: Machine intelligent mapping of cancer-beating molecules in foods.

Recent data indicate that up-to 30-40% of cancers can be prevented by dietary and lifestyle measures...

Healthcare uses of artificial intelligence: Challenges and opportunities for growth.

Forms of Artificial Intelligence (AI), like deep learning algorithms and neural networks, are being ...

Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers.

The establishment of new therapeutic strategies for metabolic syndrome is urgently needed because me...

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