AIMC Topic: Adenocarcinoma

Clear Filters Showing 71 to 80 of 238 articles

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma.

Nature communications Jun 13, 2023
Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to ...
Adenocarcinoma Humans Pancreatic Neoplasms Deep Learning
View on PubMed DOI

Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association Jun 3, 2023
INTRODUCTION: The Laurén classification is widely used for Gastric Cancer (GC) histology subtyping. However, this classification is prone to interobserver variability and its prognostic value remains controversial. Deep Learning (DL)-based assessment...
Humans Prognosis Deep Learning Adenocarcinoma Proportional Hazards Models Retrospective Studies Stomach Neoplasms
View on PubMed DOI

Novel radiomic features versus deep learning: differentiating brain metastases from pathological lung cancer types in small datasets.

The British journal of radiology May 2, 2023
OBJECTIVE: Accurate diagnosis and early treatment are crucial for survival in patients with brain metastases. This study aims to expand the capability of radiomics-based classification algorithms with novel features and compare results with deep lear...
Adenocarcinoma Deep Learning Lung Neoplasms Humans Small Cell Lung Carcinoma Brain Neoplasms
View on PubMed DOI

Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BMC bioinformatics Apr 13, 2023
BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervical adenocarcinoma patients and process personalized survival prediction.
Humans Neural Networks, Computer Deep Learning Adenocarcinoma Female Uterine Cervical Neoplasms
View on PubMed DOI

Overall mortality risk analysis for rectal cancer using deep learning-based fuzzy systems.

Computers in biology and medicine Mar 17, 2023
Colorectal cancer is a leading cause of cancer mortality worldwide, with an increasing incidence rate in developing countries. Integration of genetic information with cancer therapy guidance has shown promise in cancer treatment, indicating its poten...
Adenocarcinoma Rectal Neoplasms Humans Algorithms Risk Assessment Deep Learning
View on PubMed DOI

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

EBioMedicine Dec 26, 2022
BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.
Humans Algorithms Adenocarcinoma Carcinoma, Squamous Cell Bone Neoplasms Deep Learning
View on PubMed DOI

Detection of Colorectal Adenocarcinoma and Grading Dysplasia on Histopathologic Slides Using Deep Learning.

The American journal of pathology Dec 21, 2022
Colorectal cancer (CRC) is one of the most common types of cancer among men and women. The grading of dysplasia and the detection of adenocarcinoma are important clinical tasks in the diagnosis of CRC and shape the patients' follow-up plans. This stu...
Pathologists Hyperplasia Deep Learning Adenocarcinoma Humans Neural Networks, Computer Colorectal Neoplasms Male Female
View on PubMed DOI

Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

Nature communications Nov 2, 2022
A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, ...
Carcinoma, Squamous Cell Deep Learning Humans Adenocarcinoma Uncertainty
View on PubMed DOI

The diagnostic and prognostic value of radiomics and deep learning technologies for patients with solid pulmonary nodules in chest CT images.

BMC cancer Nov 1, 2022
BACKGROUND: Solid pulmonary nodules are different from subsolid nodules and the diagnosis is much more challenging. We intended to evaluate the diagnostic and prognostic value of radiomics and deep learning technologies for solid pulmonary nodules.
Adenocarcinoma Adenocarcinoma of Lung Deep Learning Lung Neoplasms Retrospective Studies Tomography, X-Ray Computed Humans Prognosis
View on PubMed DOI

Measuring pure ground-glass nodules on computed tomography: assessing agreement between a commercially available deep learning algorithm and radiologists' readings.

Acta radiologica (Stockholm, Sweden : 1987) Oct 31, 2022
BACKGROUND: Deep learning algorithms (DLAs) could enable automatic measurements of solid portions of mixed ground-glass nodules (mGGNs) in agreement with the invasive component sizes measured during pathologic examinations. However, the measurement o...
Adenocarcinoma of Lung Deep Learning Retrospective Studies Adenocarcinoma Tomography, X-Ray Computed Neoplasm Invasiveness Lung Neoplasms Humans Algorithms
View on PubMed DOI
Popular Topics
Recent Journals