AIMC Topic: Machine Learning

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Use of machine learning to identify prognostic variables for outcomes in chronic low back pain treatment: a retrospective analysis.

The Journal of manual & manipulative therapy
OBJECTIVES: Most patients seen in physical therapy (PT) clinics for low back pain (LBP) are treated for chronic low back pain (CLBP), yet PT interventions suggest minimal effectiveness. The Cochrane Back Review Group proposed 'Holy Grail' questions, ...

Target Fisher: A Consensus Structure-Based Target Prediction Tool, and its Application in the Discovery of Selective MAO-B Inhibitors.

Chemistry (Weinheim an der Bergstrasse, Germany)
In this work we introduce Target Fisher, a consensus structure-based target prediction tool that integrates molecular docking and machine learning with the aim to aid in the identification of potential biological targets and the optimization of the u...

Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...

Predicting Fear of Breast Cancer Recurrence in women five years after diagnosis using Machine Learning and healthcare reimbursement data from the French nationwide VICAN survey.

International journal of medical informatics
OBJECTIVE: A major concern for cancer survivors after treatment is the Fear of Cancer Recurrence (FCR), which is the fear that cancer will reappear or progress. This fear can be exacerbated by medical uncertainty about the future, leading to harmful ...

A novel technique for rapid determination of pressure injury stages using intelligent machine vision.

Geriatric nursing (New York, N.Y.)
A developed intelligent machine vision system combined with deep-learning algorithms was attempted to determine pressure injury (PI) stages rapidly. A total of 500 images were selected according to the color and texture characteristics of probable PI...

A machine learning approach to stratify patients with hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders according to disorders of gut brain interaction, comorbidities and quality of life.

Neurogastroenterology and motility
BACKGROUND: A high prevalence of disorders of gut-brain interaction (DGBI) exist in patients with hypermobile Ehlers-Danlos Syndrome (hEDS) and hypermobility spectrum disorders (HSD). However, it is unknown if clusters of hEDS/HSD patients exist whic...

Improved prognostication of overall survival after radiotherapy in lung cancer patients by an interpretable machine learning model integrating lung and tumor radiomics and clinical parameters.

La Radiologia medica
BACKGROUND: Accurate prognostication of overall survival (OS) for non-small cell lung cancer (NSCLC) patients receiving definitive radiotherapy (RT) is crucial for developing personalized treatment strategies. This study aims to construct an interpre...

Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.

Journal of assisted reproduction and genetics
PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics meth...

Role of artificial intelligence in early diagnosis and treatment of infectious diseases.

Infectious diseases (London, England)
Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising solution...

Machine learning-enhanced modeling and characterization for optimizing dietary Fiber production from Highland barley bran.

International journal of biological macromolecules
This study investigated the modification of highland barley bran through co-fermentation of Lactobacillus bulgaricus and Kluyveromyces marxianus, and developed a dynamic prediction model for DF content under these co-fermentation conditions using mac...