AIMC Topic: Aged

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Using multiple machine learning algorithms to predict spinal cord injury in patients with cervical spondylosis: a multicenter study.

Scientific reports
Degenerative cervical spondylosis, a chronic and progressive condition, has a considerable impact on global health. Spinal cord injury, a severe sequela of this disease, can result from this disease. Machine learning (ML) has emerged as a valuable to...

The diagnostic potential of proteomics and machine learning in Lyme neuroborreliosis.

Nature communications
Lyme neuroborreliosis (LNB), a nervous system infection caused by tick-borne spirochetes of the Borrelia burgdorferi sensu lato complex, is among the most frequent bacterial infections of the nervous system in Europe. Early diagnosis and continuous m...

Deep learning-based vessel and nerve recognition model for lateral lymph node dissection: a retrospective feasibility study.

Langenbeck's archives of surgery
PURPOSE: Lateral lymph node dissection for rectal cancer is challenging because of the presence of blood vessels and nerves essential for postoperative genitourinary function and leg movements. Identifying these structures during surgery is crucial. ...

Universal Atrial Fibrillation Screening Using Electrocardiographic Artificial Intelligence: A Cost-Effective Approach in Rural Communities.

Journal of medical systems
Atrial fibrillation (AF) significantly contributes to the incidence of strokes. Screening for AF enhances its detection and effective management. However, universal AF screening in rural areas poses a challenge. This study evaluates the cost-effectiv...

Evaluation of postoperative bleeding risk after dental extractions in patients on antithrombotic medication: A comparison of machine learning and clinical experience.

Clinical oral investigations
OBJECTIVES: The aim of this study was to identify high-risk dental extractions in patients taking antiplatelet (AP) medication or anticoagulants (ACs) and to compare an experienced surgeon's decisions with machine learning (ML) algorithms.

Use of machine learning for early prediction of short-term mortality in veterans with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...

Machine learning reveals distinct T-cell receptor clusters in plasma cell dyscrasias compared to healthy controls.

PloS one
T-cell receptor (TCR) repertoire diversity has been implicated in the progression and prognosis of multiple myeloma (MM). This study aimed to evaluate the association between T-cell clonality, immune response, and clinical outcomes in patients with p...

Revolutionizing cervical cancer care: the synergistic effects of hyperthermia and machine learning.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
OBJECTIVE: This study aimed to examine the impact of hyperthermia in conjunction with concurrent chemoradiotherapy (CCRT) on peripheral immune markers in patients with locally advanced cervical cancer (LACC). Additionally, we sought to predict the as...

Development of an explainable machine learning asthma prediction model using serum brominated flame retardants in a national population.

Clinical and experimental medicine
We aimed to explore the association of serum brominated flame retardant (BFR) metabolites and mixture profiles with asthma risk among US adults. Data were sourced from the National Health and Nutrition Examination Survey (NHANES), 1999-2023. Four mac...

Development of a machine learning-based prediction model for acute kidney injury associated with respiratory failure in the intensive care unit.

Clinical and experimental medicine
Acute kidney injury (AKI) is a frequent and severe complication in intensive care unit (ICU) patients with respiratory failure, associated with high mortality, prolonged hospitalization, and substantial healthcare burden. Conventional risk scores, su...