Primary Care

Obesity

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

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Walking the path of treatable traits in interstitial lung diseases.

Interstitial lung diseases (ILDs) are complex and heterogeneous diseases. The use of traditional dia...

Risk factors of early mortality in COVID-19 patients in Indonesia: A retrospective cohort study in a provincial referral hospital of Aceh.

Some of coronavirus disease 2019 (COVID-19) patients died after being hospitalized and early mortali...

Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.

Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Cou...

A fixed dose approach to thrombosis chemoprophylaxis may be inadequate in heavier critically ill patients.

Overweight patients are at greater risk of venous thromboembolism. We aimed to describe prescribing...

Ultra-fast deep-learned CNS tumour classification during surgery.

Central nervous system tumours represent one of the most lethal cancer types, particularly among chi...

Outcomes of totally robotic Roux-en-Y gastric bypass in patients with BMI ≥ 50 kg/m: can the robot level out "traditional" risk factors?

Roux-en-Y gastric bypass (RYGB) in patients with body mass index (BMI) ≥ 50 kg/m is a challenging pr...

Orthodontic Aligners: Current Perspectives for the Modern Orthodontic Office.

Orthodontic aligners are changing the practice of orthodontics. This system of orthodontic appliance...

An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence.

BACKGROUND: There is considerable geographic heterogeneity in obesity prevalence across counties in ...

Assessing the accuracy and completeness of artificial intelligence language models in providing information on methotrexate use.

We aimed to assess Large Language Models (LLMs)-ChatGPT 3.5-4, BARD, and Bing-in their accuracy and ...

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genet...

EXIST: EXamining rIsk of excesS adiposiTy-Machine learning to predict obesity-related complications.

BACKGROUND: Obesity is associated with an increased risk of multiple conditions, ranging from heart ...

Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI.

OBJECTIVE: This study aimed to evaluate the image quality and lesion conspicuity of the deep learnin...

Early Prediction of Progression to Alzheimer's Disease using Multi-Modality Neuroimages by a Novel Ordinal Learning Model ADPacer.

Machine learning has shown great promise for integrating multi-modality neuroimaging datasets to pre...

A comparison of perioperative outcomes of transperitoneal versus retroperitoneal robot-assisted partial nephrectomy: a systematic review.

RAPN can be carried out via a transperitoneal or retroperitoneal approach. The choice between the tw...

A Comparative Analysis of Various Machine Learning Algorithms to Improve the Accuracy of HbA1c Estimation Using Wrist PPG Data.

Due to the inconvenience of drawing blood and the possibility of infection associated with invasive ...

Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.

The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for ...

Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.

AIM: To study the existence of subgroups by exploring the similarities between the attributes of the...

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