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Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality globally, primarily due to its late diagnosis. Early detection is crucial yet challenging. This study leverages the potential of deep learning (DL) techn...

[Identification of osteoid and chondroid matrix mineralization in primary bone tumors using a deep learning fusion model based on CT and clinical features: a multi-center retrospective study].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
METHODS: We retrospectively collected CT scan data from 276 patients with pathologically confirmed primary bone tumors from 4 medical centers in Guangdong Province between January, 2010 and August, 2021. A convolutional neural network (CNN) was emplo...

Risk prediction of integrated traditional Chinese and western medicine for diabetes retinopathy based on optimized gradient boosting classifier model.

Medicine
In order to take full advantage of traditional Chinese medicine (TCM) and western medicine, combined with machine learning technology, to study the risk factors and better risk prediction model of diabetic retinopathy (DR), and provide basis for the ...

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (...

Accurate and Efficient Algorithm for Detection of Alzheimer Disability Based on Deep Learning.

Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology
BACKGROUND/AIMS: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early detection is crucial for timely intervention and improved patient outcomes. However, traditional diagnos...

Machine Learning Reveals the Contribution of Lipoproteins to Liver Triglyceride Content and Inflammation.

The Journal of clinical endocrinology and metabolism
CONTEXT: Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease worldwide and is strongly associated with metabolic comorbidities, including dyslipidemia.

Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.

The Journal of clinical endocrinology and metabolism
CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.

segcsvd: A Convolutional Neural Network-Based Tool for Quantifying White Matter Hyperintensities in Heterogeneous Patient Cohorts.

Human brain mapping
White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MRI)-based biomarker of cerebral small vessel disease (CSVD). WMH are associated with cognitive decline and increased risk of stroke and dementia, and a...

The effectiveness of care robots in alleviating physical burden and pain for caregivers: Non-randomized prospective interventional study - Preliminary study.

Medicine
BACKGROUND: Caregiver burden significantly affects both patients and caregivers but is often overlooked in clinical practice. Physical and emotional strain on caregivers can compromise the quality of care. Care robots are emerging as solutions to all...