AIMC Topic: Disease Progression

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Exploring oculomotor challenges in amyotrophic lateral sclerosis: a comprehensive review.

Amyotrophic lateral sclerosis & frontotemporal degeneration
Traditionally understood as a motor neuron disease, amyotrophic lateral sclerosis (ALS) is now recognized to involve broader neurodegenerative processes, including the oculomotor system. This narrative review summarizes current evidence on oculomotor...

Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-regurgitation study.

European heart journal
BACKGROUND AND AIMS: Classification and risk stratification in aortic (AR), mitral (MR), and tricuspid regurgitation (TR) remains a significant clinical challenge. This study aimed to develop an artificial intelligence (AI) system to assess valvular ...

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...

Cells Keep Diverse Company in Diseased Tissues.

Cancer research
Emerging spatial profiling technologies have revolutionized our understanding of how tissue architecture shapes disease progression, yet the contribution of cellular diversity remains underexplored. In this issue, Ding and colleagues introduce multio...

Volatomics for Diagnosis and Risk Stratification of MASLD: A Proof-Of-Concept Study.

Alimentary pharmacology & therapeutics
BACKGROUND AND AIMS: Human breath contains numerous volatile organic compounds (VOCs) produced by physiological and metabolic processes or perturbed in pathological states. Electronic nose (eNose) technology has been extensively validated as a non-in...

Computational modeling of breast tissue mechanics and machine learning in cancer diagnostics: enhancing precision in risk prediction and therapeutic strategies.

Expert review of anticancer therapy
INTRODUCTION: Breast cancer remains a significant global health issue. Despite advances in detection and treatment, its complexity is driven by genetic, environmental, and structural factors. Computational methods like Finite Element Modeling (FEM) h...

Unveiling Prognostic and Diagnostic Biomarkers in Knee and Hip Osteoarthritis: A Targeted Review.

Discovery medicine
Osteoarthritis is a multifactorial condition marked by the gradual deterioration of joint cartilage, synovial inflammation, alterations in the subchondral bone and changes in the surrounding soft tissues. Clinical assessments and patient-reported out...

Machine learning prediction prior to onset of mild cognitive impairment using T1-weighted magnetic resonance imaging radiomic of the hippocampus.

Asian journal of psychiatry
BACKGROUND: Early identification of individuals who progress from normal cognition (NC) to mild cognitive impairment (MCI) may help prevent cognitive decline. We aimed to build predictive models using radiomic features of the bilateral hippocampus in...

Evolution of Cortical Lesions and Function-Specific Cognitive Decline in People With Multiple Sclerosis.

Neurology
BACKGROUND AND OBJECTIVES: Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-speci...

Machine learning predictions of tumor progression: How reliable are we?

Computers in biology and medicine
BACKGROUND: Cancer continues to pose significant challenges in healthcare due to the complex nature of tumor progression. In this digital era, artificial intelligence has emerged as a powerful tool that can potentially transform multiple aspects of c...