Oncology/Hematology

Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.

Glioma is a highly malignant brain tumor with limited treatment options. We employed the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to predict new glioma therapies. We began by computing interaction scores between extensive libraries of drugs/compounds and proteins to generate "interaction signatures" that model compound behavior on a p...

Bone Magnetic Resonance Imaging: From Conventional Methods to AI-Driven Solutions.

With global population aging and increased life expectancy, bone diseases affect a substantial proportion of individuals worldwide, imposing a significant socioeconomic burden. Although X-ray-based imaging techniques remain the clinical standard for bone assessment, they are constrained by ionizing radiation exposure and poor soft-tissue contrast. Magnetic resonance imaging (MRI) has emerged as a ...

CMML2AML: machine-learning discovery of co-mutations and specific single mutations predictive of blast transformation in chronic myelomonocytic leukemia.

Contemporary risk models in chronic myelomonocytic leukemia (CMML) focus on the prognostic relevance of individual rather than concurrent mutations. I...

Wooden-Tip Electrospray Ionization Mass Spectrometry Combined With Machine Learning for Differentiating Thyroid Tumours.

Direct mass spectrometry (MS) analysis of human tissues at the molecular level has great potential for clinical diagnosis and biomarker discovery. How...

Content analysis of output from generative artificial intelligence chatbots when prompted about breast cancer and alcohol consumption.

OBJECTIVES: Alcohol is a group one carcinogen and contributes to breast cancer risk for women. Awareness of this relationship remains low. Generative ...

Generative deep learning-driven de novo design of targeted MAP4K6 inhibitors.

The discovery of selective small-molecule inhibitors for pharmacologically underexplored kinases remains a critical barrier to precision drug developm...

Accurate diagnosis of non-small cell and small cell lung cancer by using machine learning models trained with physical science features extracted from pathological images.

BACKGROUND: Accurate differentiation between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) is crucial for optimising treatment ...

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genom...

Pathology-Anchored Transcranial Sonography: A Cascaded Super-Resolution Deep Learning System for Early-Stage Parkinson's Disease Grading.

Delayed diagnosis of Parkinson's disease (PD) due to undetectable early pathological changes remains a major clinical challenge limiting effective tre...

Multimodal deep feature fusion with transformer for brain tumor classification from magnetic resonance imaging.

Brain tumors (BTs) arise due to abnormal cell growth, which has a high mortality rate globally. Millions of lives can be saved through the timely iden...

Deep learning-based automated masseter muscle area on routine CT stratifies survival in oral cancer.

OBJECTIVES: To develop and validate a deep learning model for automated masseter muscle segmentation on routine head and neck CT and to evaluate wheth...

High-throughput strategy for targeting MDM2 in uveal melanoma to reverse radiation therapy resistance.

Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy comb...

Accurate prediction of ecDNA in interphase cancer cells using deep neural networks.

Oncogene amplification is a key driver of cancer pathogenesis and is often mediated by extrachromosomal DNA (ecDNA). EcDNA amplifications are associat...

Smart hydrogels for overcoming cancer multidrug resistance.

Multidrug resistance (MDR) remains the principal impediment to curative oncology, driven by complex interplays between cancer cells and the tumor micr...

Baseline pain, fatigue, and sleep quality predict 12-week pain improvement in inflammatory arthritis: retrospective real-world analysis of a digital health application cohort.

UNLABELLED: Despite advances in pharmacotherapy, many patients with inflammatory arthritis (IA) experience residual pain even in remission. Digital he...

Bacterial taxa associated with lung cancer cases in Southeast Asians: a pilot case-control study.

PURPOSE: Lung cancer is the leading cause of cancer-related mortality worldwide, yet its underlying mechanisms remain unclear. Disruptions in the resp...

Clinical relevance of the characterisation and quantification of CD8+ T-cell infiltration in high-grade serous ovarian carcinoma using machine learning-based image analysis of dual immunostaining.

INTRODUCTION: High-grade serous carcinoma (HGSC) is the most common and aggressive subtype of ovarian cancer. Although tumour stage and complete cytor...

Artificial Intelligence Across the PSMA Theranostic Continuum in Prostate Cancer.

Prostate cancer is among the most common male malignancies worldwide, with recent advances in molecular imaging and targeted radiopharmaceutical thera...

Deep learning on genome-wide association studies to predict the patient-specific risk of radiation-induced erectile dysfunction.

OBJECTIVE: Radiation-induced erectile dysfunction (RIED) is a frequent, unpredictable complication following radiotherapy for prostate cancer. We hypo...

Scoparone alleviates cisplatin-induced acute kidney injury by inhibiting 5-lipoxygenase-mediated ferroptosis.

Ferroptosis, a regulated form of cell death, plays a critical role in renal tubular epithelial cells during acute kidney injury (AKI). Scoparone, a bi...