AIMC Topic: Patient Selection

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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...

Artificial intelligence and nonoperating room anesthesia.

Current opinion in anaesthesiology
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) in nonoperating room anesthesia (NORA) represents a timely and significant advancement. As the demand for NORA services expands, the application of AI is poised to improve patient sel...

A multiview deep learning-based prediction pipeline augmented with confident learning can improve performance in determining knee arthroplasty candidates.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Preoperative prudent patient selection plays a crucial role in knee osteoarthritis management but faces challenges in appropriate referrals such as total knee arthroplasty (TKA), unicompartmental knee arthroplasty (UKA) and nonoperative inte...

[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...

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...

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...

Revolutionizing clinical trials: the role of AI in accelerating medical breakthroughs.

International journal of surgery (London, England)
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...

An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BackgroundEMBOLISE (NCT04402632) is an ongoing randomized controlled trial investigating the safety and efficacy of middle meningeal artery embolization for the treatment of subacute or chronic subdural hematoma (SDH). Viz RECRUIT SDH is an artificia...

Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer.

Medical physics
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...