Latest AI and machine learning research in oncology/hematology for healthcare professionals.
A machine learning-guided strategy, which integrated unsupervised structural clustering to identify diverse scaffolds for molecular hybridization followed by synergistic QSAR and molecular docking screening, identified lead compound 7. Guided by this lead, a series of thieno[2,3-d]pyrimidine derivatives were developed as menin inhibitors through several rounds of rational structural optimization. ...
PURPOSE: Programmed cell death ligand-1 (PD-L1) is a key prognostic and predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). This study aimed to develop a machine-learning model using CT-based radiomic features to predict PD-L1 expression status in NSCLC patients. MATERIALS AND METHODS: This retrospective study included 215 patients (mean age, 63.4 ± 9.1 years; range, 36-8...
Cancer immunotherapies trigger highly variable responses in patients and in genetically identical mouse models. To assess the intrinsic stochasticity ...
Recent controversy in the cancer microbiome field highlights the need for more reliable microbial detection from human genomic data. Here, we develop ...
T cells are central to the adaptive immune response, capable of detecting pathogenic antigens while ignoring healthy tissues with remarkable specifici...
OBJECTIVE: Despite advances in mammography screening, some cancers remain undetected, prompting the evaluation of artificial intelligence (AI) as an i...
BACKGROUND: Oxaliplatin resistance significantly impairs therapeutic outcomes in colorectal cancer. However, reliable diagnostic markers for early det...
BACKGROUND: Patients with locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (NCRT) and subsequently experience early rec...
Colorectal cancer (CRC) remains a significant global health concern and is among the leading causes of cancer-related mortality. The disease often pro...
PURPOSE OF REVIEW: To examine recent advances in understanding breast cancer brain metastases (BCBM), with emphasis on metastatic mechanisms, tumour-m...
This study aimed to evaluate the clinical validity of a dose-mimicking automated planning for volumetric-modulated arc therapy (VMAT) in patients with...
BACKGROUND: Artificial intelligence (AI) applications in endoscopy, particularly computer-aided detection (CADe), have shown consistent benefit in ran...
OBJECTIVE: Tumor Treating Fields (TTFields) is an emerging cancer therapy whose efficacy is closely linked to the electric field (EF) intensity delive...
Tropomyosin receptor kinase A (TrkA), a high-affinity receptor for nerve growth factor (NGF), is implicated in nociception and local angiogenesis. We ...
BACKGROUND: Early-stage clinical findings often appear only as conference posters circulated on social media. Because posters rarely carry structured ...
The advent of long-axial-field-of-view (LAFOV) PET/CT systems has significantly improved whole-body imaging by providing higher sensitivity and extend...
Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, primar...
Cancer organoids and cancer spheroids are 3D cell culture models with distinct yet overlapping purposes in cancer research. Various commercially avail...
Brown adipose tissue (BAT) plays a key role in energy metabolism and cardiometabolic health. Its detection typically relies on 18F-FDG PET, which is c...