AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Machine learning approach for unmet medical needs among middle-aged adults in South Korea: a cross-sectional study.

BMC health services research
BACKGROUND: South Korea is reported to have higher levels of unmet medical needs (UMN) than other countries, particularly among the middle-aged adult population. Considering that this group constitutes a substantial portion of the country's productiv...

Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction.

BMC medical informatics and decision making
BACKGROUND: Differentiated thyroid cancer (DTC) is a common endocrine malignancy with rising incidence and frequent recurrence, despite a generally favorable prognosis. Accurate recurrence prediction is critical for guiding post-treatment strategies....

Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning.

Respiratory research
BACKGROUND: Pneumonia is a major threat to the health of children, especially those under the age of five. Mycoplasma  pneumoniae infection is a core cause of pediatric pneumonia, and the incidence of severe mycoplasma pneumoniae pneumonia (SMPP) has...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BMC public health
BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) could be the first Disease X; therefore, understanding the epidemiological experiences of COVID-19 is c...

Improving prediction accuracy of hospital arrival vital signs using a multi-output machine learning model: a retrospective study of JSAS-registry data.

BMC emergency medicine
BACKGROUND: Critically ill patients can deteriorate rapidly; therefore, prompt prehospital interventions and seamless transition to in-hospital care upon arrival are crucial for improving survival. In Japan, helicopter emergency medical services (HEM...

An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.

Scientific reports
The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade. Three hundred forty meningiomas from one hospital composed the training set, and 102 meningiomas fr...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Scientific reports
Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disorders early is essential for effective treatment, which traditionally relies on polysomnogram (PSG) t...

Constructing a prediction model for acute pancreatitis severity based on liquid neural network.

Scientific reports
Acute pancreatitis (AP) is a common disease, and severe acute pancreatitis (SAP) has a high morbidity and mortality rate. Early recognition of SAP is crucial for prognosis. This study aimed to develop a novel liquid neural network (LNN) model for pre...

A clinically applicable AI system for detection and diagnosis of bone metastases using CT scans.

Nature communications
Manual interpretation of CT images for bone metastasis (BM) detection in primary cancer remains challenging. We present an automated Bone Lesion Detection System (BLDS) developed using CT scans from 2518 patients (9177 BMs; 12,824 non-BM lesions) acr...

Prescriptive Predictors of Mindfulness Ecological Momentary Intervention for Social Anxiety Disorder: Machine Learning Analysis of Randomized Controlled Trial Data.

JMIR mental health
BACKGROUND: Shame and stigma often prevent individuals with social anxiety disorder (SAD) from seeking and attending costly and time-intensive psychotherapies, highlighting the importance of brief, low-cost, and scalable treatments. Creating prescrip...