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Biomarkers

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Screening biomarkers for autism spectrum disorder using plasma proteomics combined with machine learning methods.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND AIMS: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention.

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network.

Computers in biology and medicine
As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective prevention and management of dementia progression. Based on the neuropathological characteristics, MCI can b...

Development of machine-learning-driven signatures for diagnosing and monitoring therapeutic response in major depressive disorder using integrated immune cell profiles and plasma cytokines.

Theranostics
Diagnosis and treatment efficacy of major depressive disorder (MDD) currently lack stable and reliable biomarkers. Previous research has suggested a potential association between immune cells, cytokines, and the pathophysiology and treatment of MDD....

Machine learning-based prediction of sarcopenia in community-dwelling middle-aged and older adults: findings from the CHARLS.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Sarcopenia is a prominent issue among aging populations and associated with poor health outcomes. This study aimed to examine the predictive value of questionnaire and biomarker data for sarcopenia, and to further develop a user-friendly ...

Discriminating fingerprints of chronic neuropathic pain following spinal cord injury using artificial neural networks and mass spectrometry analysis of female mice serum.

Neurochemistry international
Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pa...

Exploring potential ADHD biomarkers through advanced machine learning: An examination of audiovisual integration networks.

Computers in biology and medicine
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition marked by inattention and impulsivity, linked to disruptions in functional brain connectivity and structural alterations in large-scale brain networks. Although sensory...

Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.

Frontiers in endocrinology
BACKGROUND: Alzheimer's disease (AD) represents a progressive neurodegenerative disorder characterized by the accumulation of misfolded amyloid beta protein, leading to the formation of amyloid plaques and the aggregation of tau protein into neurofib...

Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) is a highly prevalent liver disease globally, with a significant risk of progressing to cirrhosis and even liver cancer. Efferocytosis, a process implicated in a broad spectrum of ch...

Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy.

Gene
The early diagnosis of diabetic retinopathy (DR) is challenging, highlighting the urgent need to identify new biomarkers. Immune responses play a crucial role in DR, yet there are currently no reports of machine learning (ML) algorithms being utilize...

Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis.

Frontiers in immunology
Artificial intelligence (AI) has meant a turning point in data analysis, allowing predictions of unseen outcomes with precedented levels of accuracy. In multiple sclerosis (MS), a chronic inflammatory-demyelinating condition of the central nervous sy...