Other Cancers

Generative adversarial networks-based Image-to-Image translation allows tumor consistency prediction from standard MR images in pituitary adenomas.

Generative adversarial networks (GANs) offer potential in cross-modality image translation, but their application in pituitary adenomas remains uncertain. This study was to assess the feasibility of a GAN-based deep learning algorithm for generating synthetic diffusion-weighted imaging (DWI) associated images and its clinical utility in predicting tumor consistency. This multicenter study included...

Decoding (digital) histopathology: The building blocks for computational researchers.

Computational Pathology is a novel discipline at the intersection of pathology and computer science, driven by the recent advances in machine learning and image analysis. Nevertheless, combining the insights from both disciplines remains challenging, particularly due to differences in technical background and language between pathologists and engineers. It is acknowledged that literature translati...

Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.

BACKGROUND: Accurate grading and prognostic assessment of glioma requires integrating key molecular biomarkers, including IDH mutation status and the ...

Machine learning-based study of breath sounds in children with asthma in remission and cough variant asthma.

BACKGROUND: Traditional auscultation, heavily dependent on the subjective judgment of physicians, can lead to variability in diagnoses. This study aim...

Benchmarking large language models in breast cancer care: agreement with radiology-led multidisciplinary tumor board decisions.

BACKGROUND: Multidisciplinary tumor boards (MDTBs) play a central role in breast cancer management by integrating imaging findings with clinical and p...

Copper transporters promote the malignant progression of glioblastoma by regulating the immunosuppressive tumour microenvironment via the SLC31A1-WNT5A axis.

BACKGROUND: The prognosis for patients with glioblastoma (GBM) remains extremely poor, a challenge largely attributable to the complex nature of its m...

Multi-omics precision diagnosis of brucellosis: Advances in biomarker discovery and clinical application.

Brucellosis, a neglected zoonosis caused by intracellular Brucella bacteria, remains a formidable global public health challenge, especially in develo...

Molecular Functions and Drug Prediction of MMP1 and TGFBR2 in Nasopharyngeal Carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is partially driven by epithelial-mesenchymal transition (EMT). We identified potential EMT-related biomark...

Mechanism-Informed Machine Learning Enables Discovery of Oncolytic Peptides for Cancer Immunotherapy.

Oncolytic peptides (OPs) represent a promising class of cancer therapeutics capable of rapidly lysing tumor cells and activating antitumor immunity. H...

Deciphering tumor metabolites: emerging technologies shaping clinical implications.

Metabolites exert pleiotropic effects that govern tumor progression. This review evaluates current platforms and technologies for metabolite detection...

Interpreting MALDI imaging data for rare types of ampullary cancer using machine learning.

Rare tumor diseases are difficult to diagnose and there is a lack of routine diagnostic procedures. Approaches must be found that allow comprehensive ...

Efficient deep learning models for oral squamous cell carcinoma classification in histopathological images.

Recent advances in deep learning have significantly improved the accuracy and efficiency of disease classification in digital pathology. Early diagnos...

Cross-cancer homologous recombination deficiency prediction from whole slide images using transfer learning.

Accurate prediction of Homologous Recombination Deficiency (HRD) is vital for personalized cancer therapy, yet genomic assays are often costly and com...

Plasma acylcarnitine dysregulation associated with CPT1-mediated metabolism contributes to oral carcinogenesis.

Growing evidence suggests that lipid metabolic reprogramming occurs in oral cancer (OC). We characterized circulating metabolic alterations associated...

Establishment of prognostic prediction model based on lipid metabolism related genes in esophageal squamous cell carcinoma by machine learning algorithms.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer-related mortality worldwide, with a high prevalence and poor prognosi...

The evolution of prostate cancer grading: from Gleason score to risk taxonomy and the artificial intelligence revolution.

Histopathological grading remains the cornerstone of risk stratification in prostate cancer, yet conventional Gleason-based assessment is limited by i...

Gliomas as network diseases: Neuron-tumor interactions, connectome disruption, and clinical implications.

BACKGROUND: Gliomas are increasingly understood as disorders of distributed brain networks rather than focal lesions confined within radiographic marg...

Engineering immune cells for next-generation therapies.

Immune cell engineering has emerged as a transformative frontier in medicine, reshaping therapeutic strategies for cancer, autoimmunity and infectious...

Decoding Parkinson's progression: A multi-modal SuStaIn ensemble approach validated on real-world PPMI data.

BACKGROUND: Parkinson's disease (PD) exhibits substantial heterogeneity in clinical presentation and longitudinal progression, complicating prognosis,...

Performance of multimodal large language models for the detection and characterization of bone lesions on radiographs.

PURPOSE: Multimodal large language models (LLMs) offer emerging capabilities in medical image interpretation; however, their efficacy in orthopedic on...