AIMC Topic: Patient Selection

Clear Filters Showing 41 to 50 of 170 articles

Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
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
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
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
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
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
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
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 ...

Ranking patients on the kidney transplant waiting list based on fuzzy inference system.

BMC nephrology
BACKGROUND: Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important challenge in kidney transplantation process. In this study, a Fuzzy Inference System (FIS) was developed ...

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...

The path to precision medicine for MS, from AI to patient recruitment: an interview with Mauricio Farez and Helen Onuorah.

Communications biology
This year’s World Brain Day is focused on stopping Multiple Sclerosis (MS). Although amazing progress has resulted in the development of relatively successful MS therapies, access to such therapies is a major problem for most of the world. In additio...