AIMC Topic: Body Mass Index

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Predicting rTMS treatment response in depression: use of machine learning models to identify the roles of metabolic and clinical factors.

Journal of affective disorders
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression in patients with major depressive disorder (MDD) and bipolar disorder (BD), but accurate prediction of treatment response remains a challenge. Th...

Age and sex-specific differences of the intrafemoral and intratibial morphology using the Citak classification in patients undergoing total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Unlike established knee phenotype classifications, the recently introduced Citak classifications describe the intrafemoral and intratibial knee morphology. The aim of this study was to evaluate the distribution of Citak types A, B and C of t...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

International journal of medical informatics
BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifestyle habits. Early identification of at-risk individuals through machine learning models-based approac...

Prediction Model for Insulin Resistance and Implications for MASLD in Youth: A Novel Marker, the Pediatric Insulin Resistance Assessment Score.

Yonsei medical journal
PURPOSE: Insulin resistance (IR) is a condition closely associated with cardiovascular risk factors and metabolic dysfunction-associated steatotic liver disease (MASLD) is emerging as a significant IR-related complication. We aimed to develop a predi...

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation.

European journal of clinical investigation
BACKGROUND: Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.

The British journal of radiology
OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with deep learning image reconstruction (DLIR) in coronary computed tomography angiography (CCTA) for slender patients with body-mass-index (BMI) ≤25 kg/m2.

Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study.

BMC cancer
BACKGROUND: Malnutrition is common in cancer patients and worsens treatment and prognosis. The Patient-Generated Subjective Global Assessment (PG-SGA) is the best tool to evaluate malnutrition, but it is complicated has limited its routine clinical u...

Processing UK Biobank High Resolution Accelerometry Data for Unsupervised Identification of Activity Profiles and Their Differences in Clinically Relevant Outcome Parameters - The ATLAS Index Revisited.

Studies in health technology and informatics
Accelerometer data obtained with wearable devices over extended periods of time provides objective, valuable information on activity behavior. Building on previous work to derive easy-to-interpret activity parameters - the Activity Types from Long-te...