AI Medical Compendium Journal:
Systematic reviews

Showing 1 to 10 of 49 articles

The effect of lower limb rehabilitation robot on lower limb -motor function in stroke patients: a systematic review and meta-analysis.

Systematic reviews
BACKGROUND: The assessment and enhancement of lower limb motor function in hemiplegic patients is of paramount importance. The emergence of lower limb rehabilitation robots offers a promising avenue for improving motor function in these patients, add...

Global output of clinical application research on artificial intelligence in the past decade: a scientometric study and science mapping.

Systematic reviews
BACKGROUND: Artificial intelligence (AI) has shown immense potential in the field of medicine, but its actual effectiveness and safety still need to be validated through clinical trials. Currently, the research themes, methodologies, and development ...

Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis.

Systematic reviews
BACKGROUND: Haemorrhagic transformation (HT) is a severe complication after ischaemic stroke, but identifying patients at high risks remains challenging. Although numerous prediction models have been developed for HT following thrombolysis, thrombect...

Semi-automated title-abstract screening using natural language processing and machine learning.

Systematic reviews
BACKGROUND: Title-abstract screening in the preparation of a systematic review is a time-consuming task. Modern techniques of natural language processing and machine learning might allow partly automatization of title-abstract screening. In particula...

Is artificial intelligence for medical professionals serving the patients?  : Protocol for a systematic review on patient-relevant benefits and harms of algorithmic decision-making.

Systematic reviews
BACKGROUND: Algorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superio...

Machine learning to optimize literature screening in medical guideline development.

Systematic reviews
OBJECTIVES: In a time of exponential growth of new evidence supporting clinical decision-making, combined with a labor-intensive process of selecting this evidence, methods are needed to speed up current processes to keep medical guidelines up-to-dat...

Title and abstract screening for literature reviews using large language models: an exploratory study in the biomedical domain.

Systematic reviews
BACKGROUND: Systematically screening published literature to determine the relevant publications to synthesize in a review is a time-consuming and difficult task. Large language models (LLMs) are an emerging technology with promising capabilities for...

Natural language processing (NLP) to facilitate abstract review in medical research: the application of BioBERT to exploring the 20-year use of NLP in medical research.

Systematic reviews
BACKGROUND: Abstract review is a time and labor-consuming step in the systematic and scoping literature review in medicine. Text mining methods, typically natural language processing (NLP), may efficiently replace manual abstract screening. This stud...

An evaluation of the Invisalign® Aligner Technique and consideration of the force system: a systematic review.

Systematic reviews
OBJECTIVE: Since its introduction 25 years ago, the Invisalign® system has undergone multiple digital and biomechanical evolutions and its effectiveness is often compared to traditional systems without considering the many differences which character...

Systematic review using a spiral approach with machine learning.

Systematic reviews
With the accelerating growth of the academic corpus, doubling every 9 years, machine learning is a promising avenue to make systematic review manageable. Though several notable advancements have already been made, the incorporation of machine learnin...