AIMC Topic: Patient Selection
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Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study.
BMC cancer
Feb 22, 2024
BACKGROUND: Artificial intelligence (AI)-assisted clinical trial screening is a promising prospect, although previous matching systems were developed in English, and relevant studies have only been conducted in Western countries. Therefore, we evalua...
Revolutionizing clinical trials: the role of AI in accelerating medical breakthroughs.
International journal of surgery (London, England)
Dec 1, 2023
Clinical trials are the essential assessment for safe, reliable, and effective drug development. Data-related limitations, extensive manual efforts, remote patient monitoring, and the complexity of traditional clinical trials on patients drive the ap...
Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer.
Medical physics
May 4, 2023
BACKGROUND: In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails co...
Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 29, 2023
Successful clinical trials offer better treatments to current or future patients and advance scientific research. Clinical trials define the target population using specific eligibility criteria to ensure an optimal enrollment sample. Clinical trial ...
Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.
BMC medical research methodology
Apr 11, 2023
BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to ...
A review of research on eligibility criteria for clinical trials.
Clinical and experimental medicine
Jan 5, 2023
The purpose of this paper is to systematically sort out and analyze the cutting-edge research on the eligibility criteria of clinical trials. Eligibility criteria are important prerequisites for the success of clinical trials. It directly affects the...
The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteria.
Scientific data
Aug 11, 2022
Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criteria are often most naturally described in free-text, using language fam...
Machine Learning Prediction of Clinical Trial Operational Efficiency.
The AAPS journal
Apr 21, 2022
Clinical trials are the gatekeepers and bottlenecks of progress in medicine. In recent years, they have become increasingly complex and expensive, driven by a growing number of stakeholders requiring more endpoints, more diverse patient populations, ...
Prediction of clinical trial enrollment rates.
PloS one
Feb 24, 2022
Clinical trials represent a critical milestone of translational and clinical sciences. However, poor recruitment to clinical trials has been a long standing problem affecting institutions all over the world. One way to reduce the cost incurred by ins...
Hospital Ownership, Geographic Region, Patient Age, Comorbidities, and Insurance Status Appear to Influence Patient Selection Robot-Assisted Ureteral Reimplantation for Benign Disease: A Population-Based Analysis.
Journal of endourology
Jan 17, 2022
Robot-assisted ureteral reimplantation (RAUR) is a relatively new minimally invasive procedure. As such, research is lacking, and the largest adult cohort studies include fewer than 30 patients. Our aim was to be the first population-based study to ...
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