Other Cancers

Construction of Immune Infiltration-Related LncRNA Signatures Based on Machine Learning for the Prognosis in Colon Cancer.

Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across gl...

Differentiating spinal pathologies by deep learning approach.

BACKGROUND CONTEXT: Spinal pathologies are diverse in nature and, excluding trauma and degenerative ...

Radiomics and artificial intelligence for soft-tissue sarcomas: Current status and perspectives.

This article proposes a summary of the current status of the research regarding the use of radiomics...

An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis.

Raman spectroscopy shows great potential as a diagnostic tool for thyroid cancer due to its ability ...

Shedding light on the black box of a neural network used to detect prostate cancer in whole slide images by occlusion-based explainability.

Diagnostic histopathology faces increasing demands due to aging populations and expanding healthcare...

A Structure-Aware Hierarchical Graph-Based Multiple Instance Learning Framework for pT Staging in Histopathological Image.

Pathological primary tumor (pT) stage focuses on the infiltration degree of the primary tumor to sur...

Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning.

INTRODUCTION: Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select n...

Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinica...

Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning im...

A Combined Model Integrating Radiomics and Deep Learning Based on Contrast-Enhanced CT for Preoperative Staging of Laryngeal Carcinoma.

RATIONALE AND OBJECTIVES: Accurate staging of laryngeal carcinoma can inform appropriate treatment d...

Accuracy of liver metastasis detection and characterization: Dual-energy CT versus single-energy CT with deep learning reconstruction.

PURPOSE: To assess whether image quality differences between SECT (single-energy CT) and DECT (dual-...

Predicting cutaneous malignant melanoma patients' survival using deep learning: a retrospective cohort study.

BACKGROUND: Cutaneous malignant melanoma (CMM) has the worst prognosis among skin cancers, especiall...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process ...

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

In recent days, non-communicable diseases (NCDs) require more attention since they require specializ...

Point-wise spatial network for identifying carcinoma at the upper digestive and respiratory tract.

PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy d...

Managing Ulcerative Colitis and Crohn's Disease: Should the Target Be Endoscopy, Histology, or Both?

In inflammatory bowel disease (IBD), mucosal healing is the primary long-term treatment goal, encomp...

Deep learning for tumor margin identification in electromagnetic imaging.

In this work, a novel method for tumor margin identification in electromagnetic imaging is proposed ...

The power of the radiologist's last word: can deep learning models accurately differentiate between high-grade gliomas and metastasis through natural language processing on radiology reports?

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, ...

Tumor Mutation Burden-Related Histopathologic Features for Predicting Overall Survival in Gliomas Using Graph Deep Learning.

Tumor mutation burden (TMB) is a potential biomarker for evaluating the prognosis and response to im...

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathologic...