Exercise & Fitness

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to its complex non-linear metabolism and the heterogeneous nature of the solid medium. These characteristics inherently limit the simulation accuracy and...

Effect of insurance status on perioperative outcomes after robotic pancreaticoduodenectomy: a propensity-score matched analysis.

The influence of Medicaid or being uninsured is prevailingly thought to negatively impact a patient's socioeconomic and postoperative course, yet little has been published to support this claim specifically in reference to robotic pancreaticoduodenectomy. This study was undertaken to determine impact of health insurance type on perioperative outcomes in patients undergoing robotic pancreaticoduode...

A stroke prediction framework using explainable ensemble learning.

The death of brain cells occurs when blood flow to a particular area of the brain is abruptly cut off, resulting in a stroke. Early recognition of str...

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important diagnostic and therapeutic applications. High-thro...

Exploring the role of large language models in radiation emergency response.

In recent times, the field of artificial intelligence (AI) has been transformed by the introduction of large language models (LLMs). These models, pop...

The weight of BMI in impacting postoperative and oncologic outcomes in pancreaticoduodenectomy is attenuated by a robotic approach.

This study was undertaken to observe the effect of body mass index (BMI) on perioperative outcomes and survival when comparing robotic vs 'open' pancr...

Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.

In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them ...

Minimally invasive sacrocolpopexy: efficiency of robotic assistance compared to standard laparoscopy.

Minimally invasive abdominal sacrocolpopexy (SC) is the treatment of choice for symptomatic, high-grade, apical or multi-compartmental pelvic organ pr...

Artificial Intelligence and Machine Learning-Powerful Yet Underutilized Tools and Algorithms in Physical Activity and Sedentary Behavior Research.

Myoelectric, Myo-Oxygenation, and Myotonometry Changes during Robot-Assisted Bilateral Arm Exercises with Varying Resistances.

Robot-assisted bilateral arm training has demonstrated its effectiveness in improving motor function in individuals post-stroke, showing significant e...

IMU-Based Fitness Activity Recognition Using CNNs for Time Series Classification.

Mobile fitness applications provide the opportunity to show users real-time feedback on their current fitness activity. For such applications, it is e...

Risk factors and clinical significance of subcutaneous emphysema after robot-assisted laparoscopic rectal surgery: a single-center experience.

Subcutaneous emphysema (SE) is a complication of laparoscopic surgery, potentially resulting in severe respiratory failure. No reports to date have fo...

Incidence and risk factors of inguinal hernia after robot-assisted radical prostatectomy: a retrospective multicenter cohort study in Japan (the MSUG94 group).

To investigate the incidence and risk factors of inguinal hernia (IH) after robot-assisted radical prostatectomy (RARP) using a multicentric database....

Robot-assisted vs laparoscopic bariatric procedures in super-obese patients: clinical and economic outcomes.

The increased operative time and costs represent the main limitations of robotic technology application to bariatric surgery. Robotic platforms may he...

Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential.

Digital whole slides images contain an enormous amount of information providing a strong motivation for the development of automated image analysis to...

Comprehensiveness, Accuracy, and Readability of Exercise Recommendations Provided by an AI-Based Chatbot: Mixed Methods Study.

BACKGROUND: Regular physical activity is critical for health and disease prevention. Yet, health care providers and patients face barriers to implemen...

Higher rating of perceived exertion and lower perceived recovery following a graded exercise test during menses compared to non-bleeding days in untrained females.

The underrepresentation of the female population in exercise sciences could be attributed, at least in part, to difficulty in appropriately accounting...

Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients.

To develop a risk score model for the occurrence of composite cardiovascular events (CVE) in patients with stable angina pectoris (SA) combined with ...

Understanding the role of emotion in decision making process: using machine learning to analyze physiological responses to visual, auditory, and combined stimulation.

Emotions significantly shape decision-making, and targeted emotional elicitations represent an important factor in neuromarketing, where they impact a...

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using th...