AIMC Topic: Neoplasms

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Enhancing Malignancy Detection and Tumor Classification in Pathology Reports: A Comparative Evaluation of Large Language Models.

Studies in health technology and informatics
BACKGROUND: Cancer registries require accurate and efficient documentation of malignancies, yet current manual methods are time-consuming and error-prone.

Development of a Synthetic Oncology Pathology Dataset for Large Language Model Evaluation in Medical Text Classification.

Studies in health technology and informatics
BACKGROUND: Large Language Models (LLMs) offer promising applications in oncology pathology report classification, improving efficiency, accuracy, and automation. However, the use of real patient data is restricted due to legal and ethical concerns, ...

Artificial Intelligence in Cancer Care: Addressing Challenges and Health Equity.

Oncology (Williston Park, N.Y.)
Overdiagnosis in cancer care remains a significant concern, often resulting in unnecessary physical, emotional, and financial burdens on patients. Artificial intelligence (AI) has the potential to address this challenge by enabling more accurate, per...

New horizons at the interface of artificial intelligence and translational cancer research.

Cancer cell
Artificial intelligence (AI) is increasingly being utilized in cancer research as a computational strategy for analyzing multiomics datasets. Advances in single-cell and spatial profiling technologies have contributed significantly to our understandi...

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...

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...

Medical accuracy of artificial intelligence chatbots in oncology: a scoping review.

The oncologist
BACKGROUND: Recent advances in large language models (LLM) have enabled human-like qualities of natural language competency. Applied to oncology, LLMs have been proposed to serve as an information resource and interpret vast amounts of data as a clin...

Validation of a Microfluidic Device Prototype for Cancer Detection and Identification: Circulating Tumor Cells Classification Based on Cell Trajectory Analysis Leveraging Cell-Based Modeling and Machine Learning.

International journal for numerical methods in biomedical engineering
Microfluidic devices (MDs) present a novel method for detecting circulating tumor cells (CTCs), enhancing the process through targeted techniques and visual inspection. However, current approaches often yield heterogeneous CTC populations, necessitat...

Applications, challenges and future directions of artificial intelligence in cardio-oncology.

European journal of clinical investigation
BACKGROUND: The management of cardiotoxicity related to cancer therapies has emerged as a significant clinical challenge, prompting the rapid growth of cardio-oncology. As cancer treatments become more complex, there is an increasing need to enhance ...

A robust ensemble framework for anticancer peptide classification using multi-model voting approach.

Computers in biology and medicine
Anticancer peptides (ACPs) hold great potential for cancer therapeutics, yet accurately identifying them remains a challenging task due to the complexity of peptide sequences and their interactions with biological systems. In this study, we propose a...