AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Multidisciplinary cancer disease classification using adaptive FL in healthcare industry 5.0.

Scientific reports
Emerging Industry 5.0 designs promote artificial intelligence services and data-driven applications across multiple places with varying ownership that need special data protection and privacy considerations to prevent the disclosure of private inform...

Deep learning applied to dose prediction in external radiation therapy: A narrative review.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Over the last decades, the use of artificial intelligence, machine learning and deep learning in medical fields has skyrocketed. Well known for their results in segmentation, motion management and posttreatment outcome tasks, investigations of machin...

Cancer cytogenetics in the era of artificial intelligence: shaping the future of chromosome analysis.

Future oncology (London, England)
Artificial intelligence (AI) has rapidly advanced in the past years, particularly in medicine for improved diagnostics. In clinical cytogenetics, AI is becoming crucial for analyzing chromosomal abnormalities and improving precision. However, existin...

Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection.

Computers in biology and medicine
The identification of tumors through gene analysis in microarray data is a pivotal area of research in artificial intelligence and bioinformatics. This task is challenging due to the large number of genes relative to the limited number of observation...

Artificial intelligence methods available for cancer research.

Frontiers of medicine
Cancer is a heterogeneous and multifaceted disease with a significant global footprint. Despite substantial technological advancements for battling cancer, early diagnosis and selection of effective treatment remains a challenge. With the convenience...

Occlusion enhanced pan-cancer classification via deep learning.

BMC bioinformatics
Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue ...

Transfer learning may explain pigeons' ability to detect cancer in histopathology.

Bioinspiration & biomimetics
Pigeons' unexpected competence in learning to categorize unseen histopathological images has remained an unexplained discovery for almost a decade (Levenson2015e0141357). Could it be that knowledge transferred from their bird's-eye views of the earth...

Solving the puzzle of quality of life in cancer: integrating causal inference and machine learning for data-driven insights.

Health and quality of life outcomes
BACKGROUND: Understanding the determinants of global quality of life in cancer patients is crucial for improving their overall well-being. While correlations between various factors and quality of life have been established, the causal relationships ...

Application of artificial intelligence in cancer diagnosis and tumor nanomedicine.

Nanoscale
Cancer is a major health concern due to its high incidence and mortality rates. Advances in cancer research, particularly in artificial intelligence (AI) and deep learning, have shown significant progress. The swift evolution of AI in healthcare, esp...

Principles of artificial intelligence in radiooncology.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: In the rapidly expanding field of artificial intelligence (AI) there is a wealth of literature detailing the myriad applications of AI, particularly in the realm of deep learning. However, a review that elucidates the technical principles of...