Oncology/Hematology

Artificial intelligence-assisted volume isotropic simultaneous interleaved bright- and black-blood examination for brain metastases.

PURPOSE: To verify the effectiveness of artificial intelligence-assisted volume isotropic simultaneo...

Evaluation of tumor budding with virtual panCK stains generated by novel multi-model CNN framework.

As the global incidence of cancer continues to rise rapidly, the need for swift and precise diagnose...

Reconstruct incomplete relation for incomplete modality brain tumor segmentation.

Different brain tumor magnetic resonance imaging (MRI) modalities provide diverse tumor-specific inf...

Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.

OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) v...

MMFSyn: A Multimodal Deep Learning Model for Predicting Anticancer Synergistic Drug Combination Effect.

Combination therapy aims to synergistically enhance efficacy or reduce toxic side effects and has wi...

Artificial intelligence in COPD CT images: identification, staging, and quantitation.

Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with i...

Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma.

Macrophages played an important role in the progression and treatment of head and neck squamous cell...

Enhancing cervical cancer cytology screening via artificial intelligence innovation.

A double-check process helps prevent errors and ensures quality control. However, it may lead to dec...

Enhancing colorectal cancer histology diagnosis using modified deep neural networks optimizer.

Optimizers are the bottleneck of the training process of any Convolutionolution neural networks (CNN...

Deep learning-based multimodal spatial transcriptomics analysis for cancer.

The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized canc...

Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer.

BACKGROUND: Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive...

Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses.

The druggable proteome refers to proteins that can bind to small molecules with appropriate chemical...

is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.

BACKGROUND: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Position...

Exploring the role of artificial intelligence, large language models: Comparing patient-focused information and clinical decision support capabilities to the gynecologic oncology guidelines.

Gynecologic cancer requires personalized care to improve outcomes. Large language models (LLMs) hold...

Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.

BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship b...

Perovskite Probe-Based Machine Learning Imaging Model for Rapid Pathologic Diagnosis of Cancers.

Accurately distinguishing tumor cells from normal cells is a key issue in tumor diagnosis, evaluatio...

Application of artificial intelligence in chronic myeloid leukemia (CML) disease prediction and management: a scoping review.

BACKGROUND: Navigating the complexity of chronic myeloid leukemia (CML) diagnosis and management pos...

An end-to-end deep learning method for mass spectrometry data analysis to reveal disease-specific metabolic profiles.

Untargeted metabolomic analysis using mass spectrometry provides comprehensive metabolic profiling, ...

Machine learning to predict completion of treatment for pancreatic cancer.

BACKGROUND: Chemotherapy enhances survival rates for pancreatic cancer (PC) patients postsurgery, ye...

Deep reinforcement learning in radiation therapy planning optimization: A comprehensive review.

PURPOSE: The formulation and optimization of radiation therapy plans are complex and time-consuming ...

Commentary on "Artificial Intelligence in Dermatology: A Systematic Review of Its Applications in Melanoma and Keratinocyte Carcinoma Diagnosis" and "Artificial Intelligence for Mohs and Dermatologic Surgery: A Systematic Review and Meta-Analysis".