AIMC Topic: Machine Learning

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Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.

PloS one
AIM: To study the existence of subgroups by exploring the similarities between the attributes of the nodes of the groups, in relation to diet and gender and, to analyse the connectivity between groups based on aspects of similarities between them thr...

Predicting Sociodemographic Attributes from Mobile Usage Patterns: Applications and Privacy Implications.

Big data
When users interact with their mobile devices, they leave behind unique digital footprints that can be viewed as predictive proxies that reveal an array of users' characteristics, including their demographics. Predicting users' demographics based on ...

Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective.

Computers in biology and medicine
Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases, such as skin, breast, and lung cancer. AI is an advanced form of technology that uses mathematical-based algorithmic principles similar to those of the ...

Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

Cell reports. Medicine
We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological sl...

Africa's readiness for artificial intelligence in clinical radiotherapy delivery: Medical physicists to lead the way.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: There have been several proposals by researchers for the introduction of Artificial Intelligence (AI) technology due to its promising role in radiotherapy practice. However, prior to the introduction of the technology, there are certain g...

Combining Deep Learning Neural Networks with Genetic Algorithms to Map Nanocluster Configuration Spaces with Quantum Accuracy at Low Computational Cost.

Journal of chemical information and modeling
The configuration spaces for bimetallic AuPd nanoclusters of various sizes are explored efficiently and analyzed accurately by combining genetic algorithms with neural networks trained on density functional theory. The methodology demonstrated herein...

Multi-domain knowledge graph embeddings for gene-disease association prediction.

Journal of biomedical semantics
BACKGROUND: Predicting gene-disease associations typically requires exploring diverse sources of information as well as sophisticated computational approaches. Knowledge graph embeddings can help tackle these challenges by creating representations of...

Predicting congenital renal tract malformation genes using machine learning.

Scientific reports
Congenital renal tract malformations (RTMs) are the major cause of severe kidney failure in children. Studies to date have identified defined genetic causes for only a minority of human RTMs. While some RTMs may be caused by poorly defined environmen...