AIMC Topic: Machine Learning
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The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging.
BMC medical imaging
May 22, 2025
BACKGROUND: White matter hyperintensities (WMHs) are closely associated with cognitive frailty (CF). This study aims to explore the potential diagnostic value of WMHs for CF based on radiomics approaches, thereby providing a novel methodology for the...
Transcriptome combined with Mendelian randomization to identify key genes related to polyamine metabolism in childhood obesity and elucidate their molecular regulatory mechanisms.
Scientific reports
May 22, 2025
Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the identification of key genes associated with polyamines metabolism in CO could offer fresh insights for cl...
Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways.
Scientific reports
May 22, 2025
Breast cancer is a complex and challenging disease to treat, and despite progress in combating it, drug resistance remains a significant hindrance. Drug combinations have shown promising results in improving therapeutic outcomes, and many machine lea...
Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.
Scientific reports
May 22, 2025
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...
Imputing single-cell protein abundance in multiplex tissue imaging.
Nature communications
May 22, 2025
Multiplex tissue imaging enables single-cell spatial proteomics and transcriptomics but remains limited by incomplete molecular profiling, tissue loss, and probe failure. Here, we apply machine learning to impute single-cell protein abundance using m...
The hermeneutic window and machine-based interactions in primary care: how do we prevent depersonalisation?
The British journal of general practice : the journal of the Royal College of General Practitioners
May 22, 2025
BACKGROUND: Digital technologies are transforming healthcare delivery by enhancing accessibility and providing innovative ways to manage increasing patient demand. With the rise of artificial intelligence (AI) and machine learning (ML), a tsunami of ...
Applying computational protein design to therapeutic antibody discovery - current state and perspectives.
Frontiers in immunology
May 22, 2025
Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the prol...
An improved Red-billed blue magpie feature selection algorithm for medical data processing.
PloS one
May 22, 2025
Feature selection is a crucial preprocessing step in the fields of machine learning, data mining and pattern recognition. In medical data analysis, the large number and complexity of features are often accompanied by redundant or irrelevant features,...
Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.
AMIA ... Annual Symposium proceedings. AMIA Symposium
May 22, 2025
Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surveillance documentation patterns to predict deterioration risks for hospitalized patients. In a retros...
Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex.
Cell genomics
May 21, 2025
Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the "Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Sp...
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