AIMC Topic: Male

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Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review.

Clinical imaging
PURPOSE: There are many radiological datasets for breast cancer, some which have supported the development of AI medical devices for breast cancer screening and image classification. This review aims to identify mammography datasets (including digiti...

American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.

Surgery
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...

Cross-shaped windows transformer with self-supervised pretraining for clinically significant prostate cancer detection in bi-parametric MRI.

Medical physics
BACKGROUND: Bi-parametric magnetic resonance imaging (bpMRI) has demonstrated promising results in prostate cancer (PCa) detection. Vision transformers have achieved competitive performance compared to convolutional neural network (CNN) in deep learn...

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale.

Cyberpsychology, behavior and social networking
In recent years, a plethora of artificial intelligence (AI) chatbots have been developed and made available to the public. Consequently, an increasing number of individuals are integrating AI chatbots into their daily lives for various purposes. This...

A CT-based deep learning for segmenting tumors and predicting microsatellite instability in patients with colorectal cancers: a multicenter cohort study.

La Radiologia medica
PURPOSE: To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).

Assessing greenspace and cardiovascular health through deep-learning analysis of street-view imagery in a cohort of US children.

Environmental research
BACKGROUND: Accurately capturing individuals' experiences with greenspace at ground-level can provide valuable insights into their impact on children's health. However, most previous research has relied on coarse satellite-based measurements.

A multimetric health literacy analysis of phalloplasty techniques: Comparing artificial intelligence and online resources.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: This study aims to compare the informational quality of online and artificial intelligence (AI) - sources on different phalloplasty donor sites to assess reliability and accessibility.

Prediction of the End of a Romantic Relationship in Peruvian Youth and Adults: A Machine Learning Approach.

The Journal of general psychology
This study explores the effectiveness of machine learning models in predicting the end of romantic relationships among Peruvian youth and adults, considering various socioeconomic and personal attributes. The study implements logistic regression, gra...

Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases.

NeuroImage
Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mai...

Machine learning insights on activities of daily living disorders in Chinese older adults.

Experimental gerontology
OBJECTIVE: This study on the aged population in China first used a large-scale longitudinal survey database to explore how different life factors affect their ability to engage in daily activities. We select and integrate multiple machine models to o...