AIMC Topic: Middle Aged

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Deep Learning Models for CT Segmentation of Invasive Pulmonary Aspergillosis, Mucormycosis, Bacterial Pneumonia and Tuberculosis: A Multicentre Study.

Mycoses
BACKGROUND: The differential diagnosis of invasive pulmonary aspergillosis (IPA), pulmonary mucormycosis (PM), bacterial pneumonia (BP) and pulmonary tuberculosis (PTB) are challenging due to overlapping clinical and imaging features. Manual CT lesio...

Predictive Modeling of Heart Failure Outcomes Using ECG Monitoring Indicators and Machine Learning.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
BACKGROUND: Heart failure (HF) is a major driver of global morbidity and mortality. Early identification of patients at risk remains challenging due to complex, multivariate clinical relationships. Machine learning (ML) methods offer promise for more...

Probing Social Support and Self-Disclosure Within Chinese Online Domestic Violence Support Groups: Leveraging Multiple Machine Learning Approaches.

Journal of community psychology
This study examines how domestic violence victims can effectively disclose their experiences in online support groups to receive meaningful support, and how community members can provide that support. Analyzing 3455 posts and 55,787 replies from Chin...

[A deep learning method for differentiating nasopharyngeal carcinoma and lymphoma based on MRI].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
To development a deep learning(DL) model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma(NPC) and nasopharyngeal lymphoma(NPL). The retrospective study included 142 patients with NPL and 292...

Predicting Primary Graft Dysfunction in Systemic Sclerosis Lung Transplantation Using Machine-Learning and CT Features.

Clinical transplantation
INTRODUCTION: Primary graft dysfunction (PGD) is a significant barrier to survival in lung transplant (LTx) recipients. PGD in patients with systemic sclerosis (SSc) remains especially underrepresented in research.

Assessment of the efficacy and accuracy of cervical cytology screening with the Hologic Genius Digital Diagnostics System.

Cancer cytopathology
BACKGROUND: Medical technologies powered by artificial intelligence are quickly transforming into practical solutions by rapidly leveraging massive amounts of data processed via deep learning algorithms. There is a necessity to validate these innovat...

Revisiting Abnormalities of Ventricular Depolarization: Redefining Phenotypes and Associated Outcomes Using Tree-Based Dimensionality Reduction.

Journal of the American Heart Association
BACKGROUND: Abnormal ventricular depolarization, evident as a broad QRS complex on an ECG, is traditionally categorized into left bundle-branch block (LBBB) and right bundle-branch block or nonspecific intraventricular conduction delay. This categori...

Digital Pathology Quantification of the Continuum of Cirrhosis Severity in Human Liver Biopsies.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Liver biopsy is the gold standard for assessing fibrosis in cirrhotic livers, yet cirrhosis is spatially heterogeneous and continuously remodels. This study evaluates a novel phenotypic digital pathology platform for continuous f...

Integration of Metabolomics, Lipidomics, and Machine Learning for Developing a Biomarker Panel to Distinguish the Severity of Metabolic-Associated Fatty Liver Disease.

Biomedical chromatography : BMC
Metabolic-associated fatty liver disease (MAFLD), a global health challenge linked to metabolic syndrome, requires accurate severity stratification for clinical management. Current invasive diagnostic methods limit practical implementation. This stud...

A Deep Learning Model Based on High-Frequency Ultrasound Images for Classification of Different Stages of Liver Fibrosis.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chronic hepatitis B patients.