AIMC Topic: Early Diagnosis
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A Multimodal Approach for Early Identification of Mild Cognitive Impairment and Alzheimer's Disease With Fusion Network Using Eye Movements and Speech.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 22, 2025
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to the overlap of initial symptoms with normal aging processes. Given that no cure exists and current ...
Machine Learning-Based Diagnostic Prediction Model Using T1-Weighted Striatal Magnetic Resonance Imaging for Early-Stage Parkinson's Disease Detection.
Academic radiology
Apr 18, 2025
RATIONALE AND OBJECTIVES: Diagnosing Parkinson's disease (PD) typically relies on clinical evaluations, often detecting it in advanced stages. Recently, artificial intelligence has increasingly been applied to imaging for neurodegenerative disorders....
Early prediction of sepsis associated encephalopathy in elderly ICU patients using machine learning models: a retrospective study based on the MIMIC-IV database.
Frontiers in cellular and infection microbiology
Apr 17, 2025
BACKGROUND: Sepsis associated encephalopathy (SAE) is prevalent among elderly patients in the ICU and significantly affects patient prognosis. Due to the symptom similarity with other neurological disorders and the absence of specific biomarkers, ear...
Using machine learning and electronic health record (EHR) data for the early prediction of Alzheimer's Disease and Related Dementias.
The journal of prevention of Alzheimer's disease
Apr 16, 2025
BACKGROUND: Over 6 million patients in the United States are affected by Alzheimer's Disease and Related Dementias (ADRD). Early detection of ADRD can significantly improve patient outcomes through timely treatment.
Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records.
BMC medical research methodology
Apr 16, 2025
BACKGROUND: Methods that enable early outbreak detection represent powerful tools in epidemiological surveillance, allowing adequate planning and timely response to disease surges. Syndromic surveillance data collected from primary healthcare encount...
Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.
BMC pregnancy and childbirth
Apr 14, 2025
BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically on...
Accelerometer-derived classifiers for early detection of degenerative joint disease in cats.
Veterinary journal (London, England : 1997)
Apr 9, 2025
Decreased mobility is a clinical sign of degenerative joint disease (DJD) in cats, which is highly prevalent, with 61 % of cats aged six years or older showing radiographic evidence of DJD. Radiographs can reveal morphological changes and assess join...
Explainable artificial intelligence to diagnose early Parkinson's disease via voice analysis.
Scientific reports
Apr 5, 2025
Parkinson's disease (PD) is a neurodegenerative disorder affecting motor control, leading to symptoms such as tremors and stiffness. Early diagnosis is essential for effective treatment, but traditional methods are often time-consuming and expensive....
Refining early detection of Marburg Virus Disease (MVD) in Rwanda: Leveraging predictive symptom clusters to enhance case definitions.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Apr 3, 2025
BACKGROUND: Marburg Virus Disease (MVD) poses a significant global health risk due to its high case fatality rates (24%-88%) and the diagnostic challenges posed by its nonspecific early symptoms, which overlap with other febrile illnesses like malari...
Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study.
International journal of surgery (London, England)
Apr 1, 2025
BACKGROUND: This study addresses the critical need for timely and accurate diagnosis of early postoperative infection (EPI) following cardiac surgery. EPI significantly impacts patient outcomes and healthcare costs, making its early detection vital.
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