AIMC Topic: Middle Aged

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Machine Learning-Based Diagnostic Prediction Model Using T1-Weighted Striatal Magnetic Resonance Imaging for Early-Stage Parkinson's Disease Detection.

Academic radiology
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....

Artificial neural network model enhancing the accuracy of clinical evaluation for high-risk population of lymph node metastasis in non-intestinal type early gastric cancer: a multicenter real-world study in China.

International journal of surgery (London, England)
BACKGROUND: Recent years have witnessed a proliferation of studies aimed at developing clinical models capable of predicting lymph node metastasis (LNM) in early gastric cancer (EGC), yet tools for prediction grounded in the Lauren classification rem...

Updated perspectives on visceral pleural invasion in non-small cell lung cancer: A propensity score-matched analysis of the SEER database.

Current problems in cancer
BACKGROUND: Visceral pleural invasion (VPI), including PL1 (the tumor invades beyond the elastic layer) and PL2 (the tumor extends to the surface of the visceral pleura), plays a crucial role in staging Non-Small Cell Lung Cancer (NSCLC). However, th...

Diagnostic MicroRNA Signatures to Support Classification of Pulmonary Hypertension.

Circulation. Genomic and precision medicine
BACKGROUND: Patients with pulmonary hypertension (PH) are classified based on disease pathogenesis and hemodynamic drivers. Classification informs treatment. The heart failure biomarker NT-proBNP (N-terminal pro-B-type natriuretic peptide) is used to...

Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.

Asia-Pacific journal of public health
This study aimed to develop machine learning (ML) models to predict diabetic complications in patients with type 2 diabetes (T2D) in Malaysia. Data from the Malaysian National Diabetes Registry and Death Register were used to develop predictive model...

AI-assisted identification of disability patterns within identical EDSS grades.

Multiple sclerosis (Houndmills, Basingstoke, England)
BACKGROUND: The Neurostatus-Expanded Disability Status Scale (EDSS) is the most frequently used measure of disability in multiple sclerosis (MS) trials. However, EDSS scores ⩾4.5 are mainly based on ambulation and may fail to capture relevant disabil...

Integrating Machine Learning and Follow-Up Variables to Improve Early Detection of Hepatocellular Carcinoma in Tyrosinemia Type 1: A Multicenter Study.

International journal of molecular sciences
Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to...

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients.

Journal of visualized experiments : JoVE
This study introduces a Brain-Computer Interface (BCI)-controlled upper limb assistive robot for post-stroke rehabilitation. The system utilizes electroencephalogram (EEG) and electrooculogram (EOG) signals to help users assist upper limb function in...

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model.

Journal of visualized experiments : JoVE
Lymph node status is a critical prognostic predictor for patients; however, the prognosis of colorectal signet-ring cell carcinoma (SRCC) has garnered limited attention. This study investigates the prognostic predictive capacity of the log odds of po...