AI Medical Compendium Topic

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Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review.

JMIR cancer
BACKGROUND: Natural language processing systems for data extraction from unstructured clinical text require expert-driven input for labeled annotations and model training. The natural language processing competency of large language models (LLM) can ...

Establishing Artificial Intelligence-Powered Virtual Tumor Board Meetings in Pakistan.

Cancer control : journal of the Moffitt Cancer Center
Equitable cancer care in low- and middle-income countries is crucial as mortality rates continue to rise. Artificial intelligence (AI)-powered Virtual Tumor Board Meetings (VTBMs) offer an innovative solution that facilitates real-time collaboration ...

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

PLoS computational biology
Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug...

Artificial intelligence for tumor [F]FDG-PET imaging: Advancement and future trends-part I.

Seminars in nuclear medicine
The advent of sophisticated image analysis techniques has facilitated the extraction of increasingly complex data, such as radiomic features, from various imaging modalities, including [F]FDG PET/CT, a well-established cornerstone of oncological imag...

Amogel: a multi-omics classification framework using associative graph neural networks with prior knowledge for biomarker identification.

BMC bioinformatics
The advent of high-throughput sequencing technologies, such as DNA microarray and DNA sequencing, has enabled effective analysis of cancer subtypes and targeted treatment. Furthermore, numerous studies have highlighted the capability of graph neural ...

Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One of the most promising areas of research that has potential clinical utility is the use of AI in patho...

Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) has the potential to transform cancer diagnosis, ultimately leading to better patient outcomes.

Portal dose image prediction using Monte Carlo generated transmission energy fluence maps of dynamic radiotherapy treatment plans: a deep learning approach.

Biomedical physics & engineering express
This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence ...

Advancing CAR T-cell Therapies with Artificial Intelligence: Opportunities and Challenges.

Blood cancer discovery
Artificial intelligence could enhance chimeric antigen receptor T-cell therapy outcomes through optimization of all steps, from target identification, vector design, and manufacturing to personalized data-driven clinical decisions. In this report, we...

Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy.

Progress in biomedical engineering (Bristol, England)
Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in radiotherapy, where accuracy is critical. The purpose of the study is to present patterns and develop topics in the application of AI to improve the pr...