AIMC Topic: Male

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Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.

Journal of medical imaging and radiation oncology
INTRODUCTION: Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately diagnose on preoperative imaging. This study aimed to develop and evaluate a deep learning model to pr...

Evaluating the Diagnostic Accuracy and Management Recommendations of ChatGPT in Uveitis.

Ocular immunology and inflammation
INTRODUCTION: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice...

Robot-assisted versus open radical prostatectomy: a systematic review and meta-analysis of prospective studies.

Journal of robotic surgery
The study aims to synthesize all available prospective comparative studies and reports the latest systematic analysis and updated evidence comparing robot-assisted radical prostatectomy (RARP) with open radical prostatectomy (ORP) for perioperative, ...

A deep learning system to monitor and assess rehabilitation exercises in home-based remote and unsupervised conditions.

Computers in biology and medicine
In the domain of physical rehabilitation, the progress in machine learning and the availability of cost-effective motion capture technologies have paved the way for innovative systems capable of capturing human movements, automatically analyzing reco...

Effect of real-time oxygen consumption versus fixed flow-based low flow anesthesia on oxygenation and perfusion: a randomized, single-blind study.

Medical gas research
Although low-flow anesthesia is widely used due to its various advantages, there are concerns about potential and relative hypoxia. Furthermore, oxygen is also a drug with benefits and adverse effects. We aimed to evaluate and compare the effect of r...

Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment.

European archives of psychiatry and clinical neuroscience
Ecological momentary assessment (EMA), a structured diary assessment technique, has shown feasibility to capture psychotic(-like) symptoms across different study groups. We investigated whether EMA combined with unsupervised machine learning can dist...

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...

Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning causal forest analysis.

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to identify a group of patients to have greater benefits from coronary artery bypass grafting compared ...

Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy.

Magma (New York, N.Y.)
BACKGROUND: Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have fo...