AIMC Topic: Body Mass Index
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Appraisal of adaptive neuro-fuzzy computing technique for estimating anti-obesity properties of a medicinal plant.
Computer methods and programs in biomedicine
Oct 16, 2014
This research examines the precision of an adaptive neuro-fuzzy computing technique in estimating the anti-obesity property of a potent medicinal plant in a clinical dietary intervention. Even though a number of mathematical functions such as SPSS an...
Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.
International journal of medical informatics
Sep 1, 2025
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...
Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.
European journal of radiology
Aug 1, 2025
OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical iterative reconstruction-Veo (ASiR-V) in image quality, diagnostic confidence, and intestinal lesion de...
Tomography, X-Ray Computed
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Algorithms
Retrospective Studies
Signal-To-Noise Ratio
Intestinal Diseases
Deep Learning
Body Mass Index
Radiographic Image Interpretation, Computer-Assisted
Quality Improvement
Adult
Sensitivity and Specificity
Male
Middle Aged
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
Jul 1, 2025
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
May 20, 2025
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
May 15, 2025
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...
Enhancing F-FDG PET image quality and lesion diagnostic performance across different body mass index using the deep progressive learning reconstruction algorithm.
Cancer imaging : the official publication of the International Cancer Imaging Society
May 1, 2025
BACKGROUND: As body mass index (BMI) increases, the quality of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (F-FDG) positron emission tomography (PET) images reconstructed with ordered subset expectation maximization (OSEM) declines, negatively impacting ...
Predicting Body Fat Percentage from Simple Anthropometric Measurements: A Machine Learning Approach.
Studies in health technology and informatics
Apr 8, 2025
Accurately assessing body fat percentage (BF%) is crucial for healthcare and fitness but is hindered by gold-standard methods that are costly and invasive. This study employs a dataset containing variables such as age, sex, Body Mass Index (BMI), and...
Effect of artificial intelligence driven therapeutic lifestyle changes (AI-TLC) intervention on health behavior and health among obesity pregnant women in China: a randomized controlled trial protocol.
Frontiers in public health
Jan 1, 2025
INTRODUCTION: Obesity has reached epidemic proportions globally, posing significant challenges to public health and economic stability. In China, the prevalence of obesity is increasing rapidly, particularly among pregnant women, who face unique risk...
Developing a machine learning algorithm to predict psychotropic drugs-induced weight gain and the effectiveness of anti-obesity drugs in patients with severe mental illness: Protocol for a prospective cohort study.
PloS one
Jan 1, 2025
Obesity is a global public health concern, often co-occurring in patients with severe mental illnesses. The impact of psychotropic drugs-induced weight gain is augmenting the disease burden and healthcare expenditure. However, predictors of psychotro...
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