AIMC Topic: Male

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Prostate cancer prognosis using machine learning: A critical review of survival analysis methods.

Pathology, research and practice
Prostate Cancer is a disease that affects the male reproductive system. The irregularity of the symptoms makes it hard for the clinicians to pinpoint the disease in the earlier stages. Techniques such as Machine Learning, Data Science, Deep Learning,...

Automated real-world data integration improves cancer outcome prediction.

Nature
The digitization of health records and growing availability of tumour DNA sequencing provide an opportunity to study the determinants of cancer outcomes with unprecedented richness. Patient data are often stored in unstructured text and siloed datase...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

International journal of environmental research and public health
Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine l...

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BMC medical informatics and decision making
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.

Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.

BMC medical imaging
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

Scientific reports
This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted a...

Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.

Scientific reports
The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general po...

Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...

G-Protein Signaling in Alzheimer's Disease: Spatial Expression Validation of Semi-supervised Deep Learning-Based Computational Framework.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multiomics datasets provide ...

During haptic communication, the central nervous system compensates distinctly for delay and noise.

PLoS computational biology
Physically connected humans have been shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is importa...