AIMC Topic: Biomarkers

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An artificial intelligence model predicts the survival of solid tumour patients from imaging and clinical data.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: The need for developing new biomarkers is increasing with the emergence of many targeted therapies. Artificial Intelligence (AI) algorithms have shown great promise in the medical imaging field to build predictive models. We developed a p...

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction.

International journal of molecular sciences
Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes throug...

Nuclear morphology is a deep learning biomarker of cellular senescence.

Nature aging
Cellular senescence is an important factor in aging and many age-related diseases, but understanding its role in health is challenging due to the lack of exclusive or universal markers. Using neural networks, we predict senescence from the nuclear mo...

Classification model with weighted regularization to improve the reproducibility of neuroimaging signature selection.

Statistics in medicine
Machine learning (ML) has been extensively applied in brain imaging studies to aid the diagnosis of psychiatric disorders and the selection of potential biomarkers. Due to the high dimensionality of imaging data and heterogeneous subtypes of psychiat...

Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

BioMed research international
The cell cycle is composed of a series of ordered, highly regulated processes through which a cell grows and duplicates its genome and eventually divides into two daughter cells. According to the complex changes in cell structure and biosynthesis, th...

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Cells
Cellular senescence is a hallmark of aging and a promising target for therapeutic approaches. The identification of senescent cells requires multiple biomarkers and complex experimental procedures, resulting in increased variability and reduced sensi...

Machine learning for risk stratification in kidney disease.

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate ri...

Integrated biomarker approach strongly explaining in vivo sub-lethal acute toxicity of butachlor on Labeo rohita.

Comparative biochemistry and physiology. Toxicology & pharmacology : CBP
Butachlor herbicide belongs to the family of chloroacetanilide group, widely used for control of grass and broadleaf weeds in paddy fields however, its repeated application may result in aquatic pollution. Butachlor residue has been detected in aquat...

The Patient Matters in the End(point).

Advances in therapy
Digital health technologies such as wearable sensors are increasingly being used in clinical trials. However, the endpoints created from these useful tools are wide and varied. Often, digital health technologies such as wearable sensors are used eith...