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F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.
TL;DRThe Fusion model outperformed the Radiomics and Clinical models in predicting lymphovascular invasion in colorectal cancer patients and showed good clinical utility and calibration, proving its potential as a precision m…
FULLTEXT: RESNET50 -
Identification and selection of the best artificial intelligence methods developed for detection and diagnosis of breast cancer.
[BACKGROUND] Comprehensive identification and prioritization of developed artificial intelligence methods for the detection and diagnosis of breast cancer can help to select proper techniques. This study aimed to introduce the best artifici…
FULLTEXT: RESNET50 -
Explainable Lightweight Model Using Low-Rank and Convolutional Block Attention for Pancreatic Cancer Diagnosis.
[BACKGROUND] Early and accurate pancreatic cancer (PC) detection remains a major clinical challenge. [METHODS] We introduce a novel hybrid deep learning framework for automated classification of CT images, which requires fewer computationa…
FULLTEXT: RESNET50 -
Genomic Characterization of Lung Cancer in Never-Smokers Using Deep Learning.
Despite promising results in using deep learning to infer genetic features from histologic whole-slide images (WSIs), no prior studies have specifically applied these methods to lung adenocarcinomas from subjects who have never smoked tobac…
FULLTEXT: RESNET50 -
Interpretable MRI-Based Machine Learning Model for Noninvasive Prediction of Axillary Lymph Node Metastasis After Neoadjuvant Chemotherapy in Breast Cancer.
[RATIONALE AND OBJECTIVES] Accurate prediction of axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy (NAC) remains challenging in breast cancer. This study aimed to develop an interpretable machine learning model integrati…
FULLTEXT: RESNET50 -
Imaging-Based Prediction of Key Breast Cancer Biomarkers Using Deep Learning on Digital Breast Tomosynthesis.
[OBJECTIVE] To evaluate the feasibility of using deep learning models applied to digital breast tomosynthesis (DBT) images for non-invasive prediction of breast cancer biomarkers, including estrogen receptor (ER), progesterone receptor (PR)…
FULLTEXT: RESNET50 -
Development and validation of the ultrasound-based radiomics and deep learning prognostic models for diffuse large B-cell lymphoma.
Lymphoma includes fatal hematological malignancies, with diffuse large B-cell lymphoma (DLBCL) as the most common aggressive non-Hodgkin lymphoma subtype. Accurate early identification of high-risk DLBCL patients is key for individualized t…
FULLTEXT: RESNET50 -
DuDeM: A Dual-Network Model for Early Gastric Cancer Detection Based on Capsule Endoscopy.
Early detection is critical for improving outcomes in gastric cancer, yet lesion recognition in capsule endoscopy is challenged by interference from different gastric anatomical sites, patient posture changes, and gastric peristalsis. This …
FULLTEXT: RESNET50 -
Robust Histopathology Subtyping via Perturbation Fidelity in Deep Classifier.
Deep learning for invasive lung adenocarcinoma subtyping remains vulnerable to real-world imaging perturbations. We present a margin consistency framework evaluating 203,226 patches from 143 whole-slide images across five adenocarcinoma sub…
FULLTEXT: RESNET50 -
Deep Learning Based Computer-Aided Detection of Prostate Cancer Metastases in Bone Scintigraphy: An Experimental Analysis.
Bone scintigraphy is a widely available and cost-effective modality for detecting skeletal metastases in prostate cancer, yet visual interpretation can be challenging due to heterogeneous uptake patterns, benign mimickers, and a high report…
FULLTEXT: RESNET50 -
Enhancing lung cancer classification through a double attention hybrid CNN-HiFuse approach.
[UNLABELLED] Lung cancer continues to be a predominant cause of cancer-related mortality globally. In 2022, lung cancer accounted for around 2.5 million new cases and around 1.8 million fatalities, highlighting the necessity for precise and…
FULLTEXT: RESNET50 -
A lightweight CNN for enhanced non-small cell lung cancer classification using CT scan image.
Lung cancer is a leading cause of cancer-related mortality worldwide, and its early and accurate detection is critical for improving patient outcomes. Computed tomography (CT) scans are widely used to diagnose lung cancer; however, the accu…
FULLTEXT: RESNET50 -
Transformer-enhanced deep ensemble for multi-class liver disease classification using computed tomography images.
The liver related diseases such as cirrhosis, fatty liver disease, and hepatocellular carcinoma raise significant health challenges in the world due to their increasing prevalence and their complexity in detection. This study features a dee…
FULLTEXT: RESNET50 -
Ultrasound Video-Based Deep Learning Model for Predicting Axillary Lymph Node Status and Nodal Burden in Breast Cancer.
[RATIONALE AND OBJECTIVES] Accurate preoperative assessment of axillary lymph node (ALN) status and nodal burden is crucial for individualized management of patients with breast cancer. This study aimed to develop and validate a two-stage d…
FULLTEXT: RESNET50 -
Interpretable hybrid ensemble with attention-based fusion and EAOO-GA optimization for lung cancer detection.
Lung cancer’s high mortality rate underscores the critical need for early and accurate diagnosis, as late-stage diagnoses often lead to 5-year survival rates as low as 5% compared to 56% for early detection, imposing significant economic bu…
FULLTEXT: RESNET50 -
Benchmarking multiple instance learning architectures from patches to pathology for prostate cancer detection and grading using attention-based weak supervision.
Histopathological evaluation is necessary for the diagnosis and grading of prostate cancer, which is still one of the most common cancers in men globally. Traditional evaluation is time-consuming, prone to inter-observer variability, and ch…
FULLTEXT: RESNET50 -
Development of a hybrid deep learning-based framework for liver fibrosis classification using ultrasound images.
[BACKGROUND AND AIMS] Liver fibrosis is a progressive accumulation of extracellular matrix proteins with distortion of hepatic architecture and can progress to cirrhosis or hepatocellular carcinoma. Biopsy remains the diagnostic gold standa…
FULLTEXT: RESNET50 -
Integrating Deep Feature Extraction and MRI Radiomics for Survival Prediction in Breast Cancer After Neoadjuvant Chemotherapy.
[RATIONALE AND OBJECTIVES] Breast cancer (BC) remains a leading contributor to the global cancer burden among women, with neoadjuvant chemotherapy (NAC) established as the standard of care for early-stage disease. However, substantial inter…
FULLTEXT: RESNET50 -
Classification of Pancreatic Cancer and Normal Tissue in 2D and 3D Optical Coherence Tomography Images Using Convolutional Neural Networks: A Comparative Study.
[BACKGROUND/OBJECTIVES] Early and complete (R0) surgical resection is essential for optimal outcomes in pancreatic cancer. Optical coherence tomography (OCT) combined with artificial intelligence (AI) may offer real-time intraoperative guid…
FULLTEXT: RESNET50 -
Ensemble Deep Learning-Based High-Precision Framework for Breast Cancer Detection from Histopathological Images.
: Analysis of histopathological images is the absolute standard of breast cancer diagnosis. However, modern deep learning- and ViT-based architecture still struggle to capture effective local and global discriminatory patterns that tend to …
FULLTEXT: RESNET50