Oncology/Hematology

Integrating Bulk and Single-Cell Transcriptomics with Machine Learning Reveals a Heme Metabolism-Based Panel for Lung Adenocarcinoma Chemotherapy Resistance.

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treatment resistance. This study investigates the clinical implications of heme metabolism in LUAD, focusing on its link to ferroptosis and drug sensitivity. Using multi-omics data from TCGA-LUAD, GEO databases, and a single-cell RNA-seq cohort, we identi...

AI-Driven Drug Target Screening Platform Identified Oncogene CACNA2D1 Activated by Enhancer Infestation in Epstein-Barr Virus-Associated Nasopharyngeal Carcinoma.

The management of nasopharyngeal cancer (NPC) is rapidly evolving, with immune checkpoint inhibitors emerging as a prominent treatment approach. However, drug development targeting specific molecular and cellular abnormalities in NPC has slowed. Recent advancements in artificial intelligence (AI) and bioinformatics, particularly those integrating multi-omics data, offer a more effective alternativ...

A fusocelular skin dataset with whole slide images for deep learning models.

Cutaneous spindle cell (CSC) lesions encompass a spectrum from benign to malignant neoplasms, often posing significant diagnostic challenges. Computer...

A customizable P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing.

Skin hemangioma is a tumor originating from skin blood vessels, which often occurs in infants and children. Brachytherapy with the P-based radionuclid...

A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing.

Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumor classification, aiding diagnostic and therapeuti...

Classification of lung cancer severity using gene expression data based on deep learning.

Lung cancer is one of the most prevalent diseases affecting people and is a main factor in the rising death rate. Recently, Machine Learning (ML) and ...

Signal-based AI-driven software solution for automated quantification of metastatic bone disease and treatment response assessment using Whole-Body Diffusion-Weighted MRI (WB-DWI) biomarkers in Advanced Prostate Cancer

We developed an AI-driven software solution to quantify metastatic bone disease from WB-DWI scans. Core technologies include: (i) a weakly-supervise...

Predictive Digital Twins with Quantified Uncertainty for Patient-Specific Decision Making in Oncology

Quantifying the uncertainty in predictive models is critical for establishing trust and enabling risk-informed decision making for personalized medi...

Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images

The rising incidence of skin cancer, coupled with limited public awareness and a shortfall in clinical expertise, underscores an urgent need for adv...

Computational Analysis using Multi-ligand Simultaneous Docking of Withaferin A and Garcinol Reveals Enhanced BCL-2 and AKT-1 Inhibition

Developing an effective medicine to combat cancer and elusive stem cells is crucial in the current scenario. Withaferin A and Garcinol, important ph...

An automated cascade framework for glioma prognosis via segmentation, multi-feature fusion and classification techniques.

Glioma is one of the most lethal types of brain tumors, accounting for approximately 33% of all diagnosed brain tumor cases. Accurate segmentation and...

Enhancing Climate-Driven Urban Tree Cooling with Targeted Nonclimatic Interventions.

Urban trees play a pivotal role in mitigating heat, yet the global determinants and patterns of their cooling efficiency (CE) remain elusive. Here, we...

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.

Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strateg...

AI-based prediction of flow dynamics of blood blended with gold and maghemite nanoparticles in an electromagnetic microchannel under abruptly changes in pressure gradient.

In cardiovascular research, electromagnetic fields (EMFs) induced by Riga plates are applied to study and potentially manipulate blood flow dynamics, ...

ChatGPT-4 vs. multi-disciplinary tumor board decisions for the therapeutic management of primary laryngeal cancer.

BACKGROUND: Artificial intelligence-based clinical decision support systems are promising tools for addressing the increasing complexity of oncologica...

Evaluation of an artificial intelligence noise reduction tool for conventional X-ray imaging - a visual grading study of pediatric chest examinations at different radiation dose levels using anthropomorphic phantoms.

BACKGROUND: Noise reduction tools developed with artificial intelligence (AI) may be implemented to improve image quality and reduce radiation dose, w...

The utility of low-dose pre-operative CT of ovarian tumor with artificial intelligence iterative reconstruction for diagnosing peritoneal invasion, lymph node and hepatic metastasis.

PURPOSE: Diagnosis of peritoneal invasion, lymph node metastasis, and hepatic metastasis is crucial in the decision-making process of ovarian tumor tr...

Development of an automated artificial intelligence-based tool for reticulin fibrosis assessment in bone marrow biopsies.

Bone marrow fibrosis plays a critical role in the diagnosis, prognosis, and management of haematological disorders, particularly myeloproliferative ne...

Development of macrophage M2 relate signature for predicting prognosis and immunotherapy response in ovarian cancer.

BACKGROUND: Ovarian cancer ranks as the fifth most common cause of cancer-related deaths in women worldwide. Macrophages M2 is believed to support tum...

Redefining Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer in the Era of Novel Antibody-Drug Conjugates.

The advent of next-generation antibody-drug conjugates (ADCs), particularly trastuzumab deruxtecan (T-DXd), has transformed our understanding of human...