AIMC Topic: Aged, 80 and over

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Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy.

International journal of cardiology
BACKGROUND: Takotsubo cardiomyopathy (TC) is an acute heart failure syndrome characterized by transient left ventricular dysfunction, often triggered by stress. Data on risk scores predicting mortality in TC is sparse. We developed a machine-learning...

EVALUATION OF PROGNOSTIC RISK MODELS BASED ON AGE AND COMORBIDITY IN SEPTIC PATIENTS: INSIGHTS FROM MACHINE LEARNING AND TRADITIONAL METHODS IN A LARGE-SCALE, MULTICENTER, RETROSPECTIVE STUDY.

Shock (Augusta, Ga.)
Background: Age and comorbidity significantly impact the prognosis of septic patients and inform treatment decisions. To provide clinicians with effective tools for identifying high-risk patients, this study assesses the predictive value of the age-a...

Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.

Blood
Inflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathogenesis. We performed blood-based proteomic profiling of 251 inflammatory proteins in 543 patients with newly diagnosed AML. Using a machine learning mo...

OCT in dermatology: a process for determining whether a fully diversified dataset is needed for AI model-building.

Optics letters
Optical coherence tomography (OCT) has sufficient depth penetration for detection of skin pathologies, but its detection effectiveness can be aided by the assistance of artificial intelligence (AI) modeling. AI model-building identifies pathologies b...

Developing an interpretable machine learning model for screening depression in older adults with functional disability.

Journal of affective disorders
This study utilized data from the 2020 wave of the China Health and Retirement Longitudinal Study database, selecting 4322 participants aged 60 and above as the study sample. Important predictors of depression in older adults with functional disabili...

Exploring supportive care needs of lung cancer patients in China and predicting with machine learning models.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aims to explore the level of supportive care needs among hospitalized lung cancer patients in China, explore the key influencing factors and use machine learning (ML) to develop predictive models for the level of supportive care n...

Multimarker Assessment of B-Cell and Plasma Cell Subsets and Their Prognostic Role in the Colorectal Cancer Microenvironment.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Although the association between cytotoxic T lymphocytes and favorable prognosis in colorectal cancer is well established, the prognostic significance of B lymphocytes remains more ambiguous. This study aimed to assess the characteristics an...

Deciphering Key Features of Social Resilience Versus Social Vulnerability in Later Life: A Biopsychosocial Model of Social Asymmetry.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Confronted with shrinking social networks, older adults exhibit individual differences in social adaptability, reflected as socially resilient versus socially vulnerable. The purpose of this study was to examine key features that reflect ...

Deep learning reveals pathology-confirmed neuroimaging signatures in Alzheimer's, vascular and Lewy body dementias.

Brain : a journal of neurology
Concurrent neurodegenerative and vascular pathologies pose a diagnostic challenge in the clinical setting, with histopathology remaining the definitive modality for dementia-type diagnosis. To address this clinical challenge, we introduce a neuropath...