Exercise & Fitness

Patient-Reported Outcomes for Robot-Assisted Laparoscopic Extravascular Renal Vein Stent Placements for Nutcracker Syndrome.

Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric artery (SMA) and the abdominal aorta. Nutcracker syndrome refers to the presence of nutcracker phenomenon with symptoms. Between 2016 and 2022, we performed 18 robot-assisted laparoscopic extravascular renal vein stent (RALERVS) placements. We sought to assess patient-reported outcomes of RALERVS place...

Integrating physics in deep learning algorithms: a force field as a PyTorch module.

MOTIVATION: Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation.

Genotypic-phenotypic landscape computation based on first principle and deep learning.

The relationship between genotype and fitness is fundamental to evolution, but quantitatively mapping genotypes to fitness has remained challenging. W...

[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System].

OBJECTIVE: To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated mi...

[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].

To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The ...

Development of deep-learning models for real-time anaerobic threshold and peak VO2 prediction during cardiopulmonary exercise testing.

AIMS: Exercise intolerance is a clinical feature of patients with heart failure (HF). Cardiopulmonary exercise testing (CPET) is the first-line examin...

Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical mea...

The rough but fascinating road to estimate peak exercise oxygen uptake by resting electrocardiogram-based deep learning.

Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants.

Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food production. Biotic and abiotic stresses predominan...

Identification of candidate biomarkers and molecular networks associated with Pulmonary Arterial Hypertension using machine learning and plasma multi-Omics analysis

Pulmonary arterial hypertension (PAH) is a rare but severe and life- threatening condition that primarily affects the pulmonary blood vessels and the ...

An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in TNM Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study.

To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-a...

[Establishment of comprehensive evaluation models of physical fitness of the elderly based on machine learning].

The present study aims to establish comprehensive evaluation models of physical fitness of the elderly based on machine learning, and provide an impor...

Association of Vitamin D with Risk Factors for Coronary Artery Disease.

Vitamin D safeguards cardiovascular health by reducing inflammation and susceptibility to atheroma. This study aimed to evaluate the association of co...

Shape-aware Segmentation of the Placenta in BOLD Fetal MRI Time Series.

Blood oxygen level dependent (BOLD) MRI time series with maternal hyperoxia can assess placental oxygenation and function. Measuring precise BOLD chan...

A multi-scale expression and regulation knowledge base for Escherichia coli.

Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-dow...

Automated detection of apoptotic bodies and cells in label-free time-lapse high-throughput video microscopy using deep convolutional neural networks.

MOTIVATION: Reliable label-free methods are needed for detecting and profiling apoptotic events in time-lapse cell-cell interaction assays. Prior stud...

ChatGPT: Transcending Language Limitations in Scientific Research Using Artificial Intelligence.

Health and scientific researchers in non-English speaking countries such as Pakistan, are not proficient in English, which limits their ability to com...

Generative models for protein sequence modeling: recent advances and future directions.

The widespread adoption of high-throughput omics technologies has exponentially increased the amount of protein sequence data involved in many salient...

Total Force Fitness Standardization: Leveraging Policy and Metrics to Inform and Accelerate Implementation.

Total Force Fitness (TFF) metrics inform leaders at every level as they develop and evaluate policies, practices, and programs that enable soldiers, a...

ActivePPI: quantifying protein-protein interaction network activity with Markov random fields.

MOTIVATION: Protein-protein interactions (PPI) are crucial components of the biomolecular networks that enable cells to function. Biological experimen...