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Comparative evaluation of feature reduction methods for drug response prediction.

Scientific reports
Personalized medicine aims to tailor medical treatments to individual patients, and predicting drug responses from molecular profiles using machine learning is crucial for this goal. However, the high dimensionality of the molecular profiles compared...

Development of a Predictive Model of Occult Cancer After a Venous Thromboembolism Event Using Machine Learning: The CLOVER Study.

Medicina (Kaunas, Lithuania)
: Venous thromboembolism (VTE) can be the first manifestation of an underlying cancer. This study aimed to develop a predictive model to assess the risk of occult cancer between 30 days and 24 months after a venous thrombotic event using machine lear...

AI-Enhanced Healthcare: Integrating ChatGPT-4 in ePROs for Improved Oncology Care and Decision-Making: A Pilot Evaluation.

Current oncology (Toronto, Ont.)
BACKGROUND: Since 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and education. Electronic patient-reported outcomes (ePROs) play a crucial role in monitoring cancer patie...

Precision in Parsing: Evaluation of an Open-Source Named Entity Recognizer (NER) in Veterinary Oncology.

Veterinary and comparative oncology
Integrating Artificial Intelligence (AI) through Natural Language Processing (NLP) can improve veterinary medical oncology clinical record analytics. Named Entity Recognition (NER), a critical component of NLP, can facilitate efficient data extractio...

A prospective study comparing highly qualified Molecular Tumor Boards with AI-powered software as a medical device.

International journal of clinical oncology
BACKGROUND: The implementation of cancer precision medicine in Japan is deeply intertwined with insurance reimbursement policies and requires case-by-case reviews by Molecular Tumor Boards (MTBs), which impose considerable operational burdens on heal...

From multi-omics to predictive biomarker: AI in tumor microenvironment.

Frontiers in immunology
In recent years, tumors have emerged as a major global health threat. An increasing number of studies indicate that the production, development, metastasis, and elimination of tumor cells are closely related to the tumor microenvironment (TME). Advan...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

Cancer genetics
CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-related immune responses exhibit diverse characteristics in different diseases. This study utilizes g...

Programmable ultrasound-mediated swarms manipulation of bacteria-red blood cell microrobots for tumor-specific thrombosis and robust photothermal therapy.

Trends in biotechnology
Despite the excellent advantages of biomicrorobots, such as autonomous navigation and targeting actuation, effective penetration and retention to deep lesion sites for effective therapy remains a longstanding challenge. Here, we present dual-engine c...

AI-based classification of anticancer drugs reveals nucleolar condensation as a predictor of immunogenicity.

Molecular cancer
BACKGROUND: Immunogenic cell death (ICD) inducers are often identified in phenotypic screening campaigns by the release or surface exposure of various danger-associated molecular patterns (DAMPs) from malignant cells. This study aimed to streamline t...

Implementation Strategy for Artificial Intelligence in Radiotherapy: Can Implementation Science Help?

JCO clinical cancer informatics
PURPOSE: Artificial intelligence (AI) applications in radiotherapy (RT) are expected to save time and improve quality, but implementation remains limited. Therefore, we used implementation science to develop a format for designing an implementation s...