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Clinical Trials as Topic

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Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

PloS one
Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sit...

Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study.

BMC cancer
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...

Artificial intelligence tools for optimising recruitment and retention in clinical trials: a scoping review protocol.

BMJ open
INTRODUCTION: In recent years, the influence of artificial intelligence technology on clinical trials has been steadily increasing. It has brought about significant improvements in the efficiency and cost reduction of clinical trials. The objective o...

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening].

Bulletin du cancer
INTRODUCTION: The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of a...

Characterisation of digital therapeutic clinical trials: a systematic review with natural language processing.

The Lancet. Digital health
Digital therapeutics (DTx) are a somewhat novel class of US Food and Drug Administration-regulated software that help patients prevent, manage, or treat disease. Here, we use natural language processing to characterise registered DTx clinical trials ...

AlpaPICO: Extraction of PICO frames from clinical trial documents using LLMs.

Methods (San Diego, Calif.)
In recent years, there has been a surge in the publication of clinical trial reports, making it challenging to conduct systematic reviews. Automatically extracting Population, Intervention, Comparator, and Outcome (PICO) from clinical trial studies c...

Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials.

Current opinion in structural biology
The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these...

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Nature communications
Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful de...

How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons.

Drug discovery today
AI techniques are making inroads into the field of drug discovery. As a result, a growing number of drugs and vaccines have been discovered using AI. However, questions remain about the success of these molecules in clinical trials. To address these ...