AI Medical Compendium Topic

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

Neoplasms

Showing 1 to 10 of 1991 articles

Clear Filters

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy-Related Cardiovascular Toxicity: Systematic Review.

JMIR cancer
BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into several health care sectors, including medical imaging. AI can transform how medical imaging is conducted and interpreted, especially in cardio-oncology.

High procalcitonin level is related to blood stream infections, gram-negative pathogens, and ICU admission in infections of adult febrile cancer patients.

Journal of the Egyptian National Cancer Institute
BACKGROUND: Blood stream infection (BSI) represent a life-threatening condition. Thus, we aimed to investigate the role of procalcitonin (PCT) and C-reactive protein (CRP) tests in adult febrile patients with BSI and other clinical infections in hosp...

Clinical characteristics, outcomes, and predictive modeling of patients diagnosed with immune checkpoint inhibitor therapy-related pneumonitis.

Cancer immunology, immunotherapy : CII
PURPOSE: The aim of this study is to better characterize the clinical characteristics and outcomes of patients diagnosed with Immune checkpoint Inhibitor (ICI) pneumonitis and propose predictive models.

Unravelling tumour spatiotemporal heterogeneity using spatial multimodal data.

Clinical and translational medicine
Analysing the genome, epigenome, transcriptome, proteome, and metabolome within the spatial context of cells has transformed our understanding of tumour spatiotemporal heterogeneity. Advances in spatial multi-omics technologies now reveal complex mol...

Peak analysis of cell-free RNA finds recurrently protected narrow regions with clinical potential.

Genome biology
BACKGROUND: Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understand...

Deep learning for malignant lymph node segmentation and detection: a review.

Frontiers in immunology
Radiation therapy remains a cornerstone in the treatment of cancer, with the delineation of Organs at Risk (OARs), tumors, and malignant lymph nodes playing a critical role in the planning process. However, the manual segmentation of these anatomical...

A novel approach to cancer treatment planning using inverse sum indeg index of fuzzy graphs.

Scientific reports
Fuzzy graph theory, with its ability to handle uncertainty and varying relationship strengths, offers a powerful tool for modeling and solving complex problems across diverse fields like medical, social network, biological networks, etc. The topologi...

Machine Learning for Predicting Postoperative Functional Disability and Mortality Among Older Patients With Cancer: Retrospective Cohort Study.

JMIR aging
BACKGROUND: The global cancer burden is rapidly increasing, with 20 million new cases estimated in 2022. The world population aged ≥65 years is also increasing, projected to reach 15.9% by 2050, making cancer control for older patients urgent. Surgic...

Low-cost robotic manipulation of live microtissues for cancer drug testing.

Science advances
The scarcity of human biopsies available for drug testing is a paramount challenge for developing therapeutics, disease models, and personalized treatments. Microtechnologies that combine the microscale manipulation of tissues and fluids offer the ex...

Lexical associations can characterize clinical documentation trends related to palliative care and metastatic cancer.

Scientific reports
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around palliative care in relation to metastatic cancer has changed. We analyzed inpatient clinical notes using u...