AIM: To develop and validate a combined model based on magnetic resonance imaging (MRI), and whole-slide imaging (WSI) to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer.
BACKGROUND: This study aims to build a machine learning (ML) model to predict the deterioration of neurological symptoms in Wilson's disease (WD) patients during short-term anti-copper therapy. The model combines brain T1WI MRI radiomics with clinica...
OBJECTIVE: This study developed and validated a deep learning model based on clinical and histopathological features for predicting the outcomes of diffuse large B-cell lymphoma (DLBCL).
BACKGROUND & AIM: Chronic hepatitis B (CHB) is a global public health problem affecting hundreds of millions of people and is associated with significant morbidity and mortality of liver cancer. Exosomes originate from cells and their detection in bi...
Journal of bioscience and bioengineering
Jun 4, 2025
Phage display selection has been used for directed evolution of antibody fragments. However, variants with binding affinity cannot be always identified due to undesirable enrichment of target-unrelated variants in the biopanning process. Here, our go...
Automatisms are repetitive, semi-ordered movements often observed in focal impaired awareness seizures and, less frequently, in generalized seizures with brief loss of consciousness. This study aims to improve the detection of these automatisms by op...
Sphingosine kinase 1 (SphK1) plays a pivotal role in cancer progression, metastasis, and chemotherapy resistance, making it a key target for therapeutic interventions in cancer, cardiovascular diseases, and inflammation. Machine learning models, incl...
The quest for solutions to infectious diseases and life-debilitating disease states has been ongoing for centuries now. Natural products researches have revealed bioactive compounds of plant and microbial origin that offer solutions to health conditi...
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
BACKGROUND: Evidence about the health effects of ultrafine particles (UFPs) remains limited, especially due to challenges in estimating exposure in epidemiological studies.
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