AIMC Topic: Machine Learning

Clear Filters Showing 28111 to 28120 of 34417 articles

In-silico evaluation of aging-related interventions using omics data and predictive modeling.

Ageing research reviews
A major challenge in aging research is identifying interventions that can improve lifespan and health and minimize toxicity. Clinical studies cannot usually consider decades-long follow-up periods, and therefore, in-silico evaluations using omics-bas...

From resting-state functional hippocampal centrality to functional outcome: An extended neurocognitive model of psychosis.

Psychiatry research
BACKGROUND: We previously proposed a neurocognitive model of psychosis in which reduced morphometric hippocampal-cortical connectivity precedes impaired episodic memory, social cognition, negative symptoms, and functional outcome. We provided support...

Machine learning Reveals ATM and CNOT6L as critical factors in Cataract pathogenesis.

Experimental eye research
OBJECTIVE: Cataract, a common age-related blinding eye disease, has a complex pathogenesis. This study aims to identify key genes and potential mechanisms associated with cataracts, offering new targets and insights for its prevention and treatment.

Evaluating the added value of salivary hormones in the context of menstrual cycle staging: A machine learning approach and app-implementation.

Psychoneuroendocrinology
OBJECTIVE: Salivary hormone assessment is commonly used in menstrual cycle studies, but its validity for accurate menstrual cycle staging has been questioned. In the present study, we explore possibilities and limitations of salivary hormone assessme...

Associations of the Hs-CRP/HDL-C ratio with stroke among US adults: Evidence from NHANES 2015-2018.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The high-sensitivity C-reactive protein (Hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio, which integrates insights into inflammation and lipid metabolism, serves as a comprehensive indicator. The association between this ra...

ADEPT: An advanced data exploration and processing tool for clinical data insights.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The rapid growth of clinical data creates challenges in analysis and interpretation for medical professionals. To address these issues, we developed the Advanced Data Exploration and Processing Tool (ADEPT), integrating data...

Deep learning models link local cellular features with whole-animal growth dynamics in zebrafish.

Life science alliance
Animal growth is driven by the collective actions of cells, which are reciprocally influenced in real-time by the animal's overall growth state. Whereas cell behavior and animal growth state are expected to be tightly coupled, it is not yet determine...

Machine learning approaches for predicting the small molecule-miRNA associations: a comprehensive review.

Molecular diversity
MicroRNAs (miRNAs) are evolutionarily conserved small regulatory elements that are ubiquitous in cells and are found to be abnormally expressed during the onset and progression of several human diseases. miRNAs are increasingly recognized as potentia...

Assessing real-life food consumption in hospital with an automatic image recognition device: A pilot study.

Clinical nutrition ESPEN
BACKGROUND AND AIMS: Accurate dietary intake assessment is essential for nutritional care in hospitals, yet it is time-consuming for caregivers and therefore not routinely performed. Recent advancements in artificial intelligence (AI) offer promising...

Effectiveness of Artificial Intelligence in detecting sinonasal pathology using clinical imaging modalities: a systematic review.

Rhinology
BACKGROUND: Sinonasal pathology can be complex and requires a systematic and meticulous approach. Artificial Intelligence (AI) has the potential to improve diagnostic accuracy and efficiency in sinonasal imaging, but its clinical applicability remain...