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GPT-4 in Clinical Practice: Assessing Its Capability for Symptom Extraction from Cancer Patient Notes.

Studies in health technology and informatics
Accurate extraction of patient symptoms and signs from clinical notes is essential for effective diagnosis, treatment planning, and research. In this study, we evaluate the capability of GPT-4, specifically GPT-4o, in extracting symptoms and signs fr...

Cancer Informatics: Novel Methods and Applications of Artificial Intelligence in Cancer Care Delivery.

Yearbook of medical informatics
OBJECTIVES: To summarize significant research contributions on cancer informatics published in 2023, an extensive search using PubMed/MEDLINE was conducted to identify the scientific contributions published in 2023 that address topics in cancer. The ...

Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.

Mediators of inflammation
: In recent years, the incidence of Crohn's disease (CD) has shown a significant global increase, with numerous studies demonstrating its correlation with various cancers. This study aims to identify novel biomarkers for diagnosing CD and explore the...

Advancing the frontier of artificial intelligence on emerging technologies to redefine cancer diagnosis and care.

Computers in biology and medicine
BACKGROUND: Artificial Intelligence (AI) is capable of revolutionizing cancer therapy and advancing precision oncology via integrating genomics data and digitized health information. AI applications show promise in cancer prediction, prognosis, and t...

Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling
Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...

Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.

Scientific reports
Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy population involves an initial risk stratification step to determine the...

Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity.

Cell
Chimeric antigen receptor (CAR) T cell immunotherapy represents a breakthrough in the treatment of hematological malignancies, but poor specificity has limited its applicability to solid tumors. By contrast, natural T cells harboring T cell receptors...

Development of a Machine Learning Algorithm to Predict Abnormalities in Serum Phosphate in a Large Oncology Cohort.

JCO clinical cancer informatics
PURPOSE: Serum phosphate is commonly measured in oncology patients because of the relationship between oncologic conditions and treatments with abnormal phosphate. All patients attending our institution, a large specialist oncology center, have a sta...

Design of Multi-Cancer VOCs Profiling Platform via a Deep Learning-Assisted Sensing Library Screening Strategy.

Analytical chemistry
The efficiency of sensor arrays in parallel discrimination of multianalytes is fundamentally influenced by the quantity and performance of the sensor elements. The advent of combinational design has notably accelerated the generation of chemical libr...

Leveraging Convolutional Neural Networks for Predicting Symptom Escalation in Chemotherapy Patients: A Temporal Resampling Approach.

Studies in health technology and informatics
This paper introduces a novel approach for predicting symptom escalation in chemotherapy patients by leveraging Convolutional Neural Networks (CNNs). Accurate forecasting of symptom escalation is crucial in cancer care, as it enables timely intervent...