Latest AI and machine learning research in leukemia for healthcare professionals.
OBJECTIVE: This study aimed to develop and evaluate a deep learning model based on the Vision Transformer (ViT) architecture for the automatic classification of hip X-ray images into three categories: normal bone mass, osteopenia, and osteoporosis. The goal was to explore the model's potential for early screening and auxiliary diagnosis of osteoporosis. METHODS: A total of 3016 hip anteroposterior...
UNLABELLED: T-cell leukemias and lymphomas (TCL) form a heterogeneous group of rare and often aggressive malignancies. Because of the rarity and heterogeneity of TCL subtypes, clinical trials are challenging to conduct, making pharmacogenomic studies in cell line panels critical for the discovery of targeted therapeutics. The scarcity of data repositories with integrated multiomics and drug screen...
OBJECTIVE: To develop a deep learning algorithm for semiquantification of spinal inflammation in patients with axial spondyloarthritis (SpA). METHODS:...
UNLABELLED: To identify molecular biomarkers associated with both osteoarthritis (OA) pathology and exercise response through multi-omics integration....
Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...
Traditional microfluidic chips for single-cell mechanical characterization face challenges such as cell aggregation and low throughput, limiting their...
BACKGROUND: Knee osteoarthritis (KOA) is one of the most prevalent chronic musculoskeletal disorders among the older adult population. Screening popul...
BACKGROUND: Glioma is the most common malignant primary brain tumor. Temozolomide (TMZ) is the standard first-line chemotherapy, but its efficacy is s...
PURPOSE: To develop and validate a nomogram model that can accurately differentiate fat-poor angiomyolipoma (fp-AML) from clear cell renal cell carcin...
BACKGROUND: Acute appendicitis poses diagnostic challenges due to symptom overlap with other abdominal conditions, often leading to misdiagnosis or mi...
Ovarian cancer is one of the most lethal gynecological malignancies, asymptomatic early progression, ineffective screening, and high histological hete...
BACKGROUND: Delayed chemotherapy-induced nausea and vomiting (CINV) in pediatric oncology patients is currently under-recognized. This study aims to d...
BACKGROUND AND OBJECTIVE: Deep learning-based cell segmentation and classification methods in digital pathology are critical for diagnostics but are h...
PURPOSE: Small cell lung cancer (SCLC) is a highly aggressive malignancy with a high incidence of liver metastases, particularly among elderly patient...
RATIONALE & OBJECTIVE: Generative artificial intelligence (AI) may help patients better understand the complexities of kidney transplantation. However...
BACKGROUND: Predicting chemosensitivity before treatment could help tailor neoadjuvant chemotherapy (NAC) in early breast cancer (eBC). Pathological c...
BACKGROUND: The platelet to white blood cell ratio (PWR) has shown prognostic value in many diseases. Yet its predictive utility for patients with ath...
BACKGROUND AND OBJECTIVE: White blood cells (WBCs) are key biomarkers of immune status, but current monitoring still relies on intermittent blood samp...
Accurate and early detection of Acute Lymphoblastic Leukemia (ALL) is critical for timely intervention and improved patient outcomes. However, the dev...
High-pressure homogenizers are used to disrupt oat cell aggregates in beverage processing applications. The mechanism of disruption remains poorly und...