AIMC Topic: Clinical Trials as Topic

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Relationship between spleen volume and diameter for assessment of response to treatment on CT in patients with hematologic malignancies enrolled in clinical trials.

Abdominal radiology (New York)
PURPOSE: Investigate spleen diameter (d) and volume (v) relationship in patients with hematologic malignancies (HM) by determining volumetric thresholds that best correlate to established diameter thresholds for assessing response to treatment. Explo...

Hepatitis B In Silico Trials Capture Functional Cure, Indicate Mechanistic Pathways, and Suggest Prognostic Biomarker Signatures.

Clinical pharmacology and therapeutics
In silico trials, utilizing mathematical models calibrated with clinical data, present a transformative approach to expedite drug development. We propose a virtual trial framework for chronic Hepatitis B, accurately simulating clinical protocols, pat...

Readability Assessment and Comparison of Large Language Model-Generated Summaries of Trial Descriptions on ClinicalTrials.gov.

Studies in health technology and informatics
This study evaluated the readability of ClinicalTrials.gov trial information using traditional readability measures (TRMs) and compared it to summaries generated by large language models (LLMs), specifically ChatGPT and a fine-tuned BART-Large-CNN (F...

EvidenceOutcomes: A Dataset of Clinical Trial Publications with Clinically Meaningful Outcomes.

Studies in health technology and informatics
The fundamental process of evidence extraction in evidence-based medicine relies on identifying PICO elements, with Outcomes being the most complex and often overlooked. To address this, we introduce EvidenceOutcomes, a large annotated corpus of clin...

Clinical Trial Eligibility Criteria Decomposition and Parsing with Large Language Models.

Studies in health technology and informatics
Clinical trial eligibility criteria, often presented as complex free text, pose significant challenges for automated processing. This study introduces a Decomposition and Parsing (DP) workflow to address these challenges by systematically breaking do...

[Analysis of the global registration status of clinical trials for artificial intelligence medical device].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The rapid development of artificial intelligence technology is driving profound changes in medical practice, particularly in the field of medical device application. Based on data from the U.S. clinical trials registry, this study analyzes the global...

Clinical trials reimagined: Integrating community engagement and artificial intelligence.

Med (New York, N.Y.)
In celebration of Clinical Trials Day, May 20, this collection of Voices highlights visionary perspectives on the evolving landscape of clinical research. It explores decentralized clinical trials, which bring research into participants' homes, enhan...

Validation and Derivation of miRNA-Based Germline Signatures Predicting Radiation Toxicity in Prostate Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Although radiotherapy (RT) is one of the primary treatment modalities used in the treatment of cancer, patients often experience toxicity during or after treatment. RT-induced genitourinary (GU) toxicity is a significant survivorship challen...

Clinical Trial Design Approach to Auditing Language Models in Health Care Setting.

JCO clinical cancer informatics
PURPOSE: Rapid advancements in natural language processing have led to the development of sophisticated language models. Inspired by their success, these models are now used in health care for tasks such as clinical documentation and medical record c...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field. For example, AI-driven adaptive trial designs may allow for real-time modifications based on emergi...