AIMC Topic: Humans

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iACP-DFSRA: Identification of Anticancer Peptides Based on a Dual-channel Fusion Strategy of ResCNN and Attention.

Journal of molecular biology
Anticancer peptides (ACPs) have been widely applied in the treatment of cancer owing to good safety, rational side effects, and high selectivity. However, the number of ACPs that have been experimentally validated is limited as identification of ACPs...

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

Thoracic cancer
BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype...

Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...

Machine-Learning Application for Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease Using Laboratory and Body Composition Indicators.

Archives of Iranian medicine
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significant global health burden without established curative therapies. Early detection and preventive strategies are crucial for effective MASLD management. T...

Synergistic pathways for health investment and economic development in China: a fuzzy-set qualitative comparative analysis.

Frontiers in public health
BACKGROUND: System coordination is an effective way to achieve high-quality development, and the debate on the interaction between health investment and economic development is still ongoing. To strengthen previous research and offer feasible advice ...

Precision Epidemiology: A Computational Analysis of the Impact of Algorithmic Prediction on the Relationship Between Population Epidemiology and Clinical Epidemiology.

International journal of public health
OBJECTIVES: Precision Medicine (PM) uses advanced Machine Learning (ML) techniques and big data to develop personalized treatments, but healthcare still relies on traditional statistical procedures not targeted on individuals. This study investigates...

A machine learning approach in a monocentric cohort for predicting primary refractory disease in Diffuse Large B-cell lymphoma patients.

PloS one
INTRODUCTION: Primary refractory disease affects 30-40% of patients diagnosed with DLBCL and is a significant challenge in disease management due to its poor prognosis. Predicting refractory status could greatly inform treatment strategies, enabling ...

Breast tumor segmentation using neural cellular automata and shape guided segmentation in mammography images.

PloS one
PURPOSE: Using computer-aided design (CAD) systems, this research endeavors to enhance breast cancer segmentation by addressing data insufficiency and data complexity during model training. As perceived by computer vision models, the inherent symmetr...

Detection of Low Resilience Using Data-Driven Effective Connectivity Measures.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Conventional thresholding techniques for graph theory analysis, such as absolute, proportional and mean degree, have often been used in characterizing human brain networks under different mental disorders, such as mental stress. However, these approa...