AIMC Topic: Deep Learning
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Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study.
BMC medical informatics and decision making
Jun 5, 2025
BACKGROUND: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patients.
A radiogenomics study on F-FDG PET/CT in endometrial cancer by a novel deep learning segmentation algorithm.
BMC cancer
Jun 5, 2025
OBJECTIVE: To create an automated PET/CT segmentation method and radiomics model to forecast Mismatch repair (MMR) and TP53 gene expression in endometrial cancer patients, and to examine the effect of gene expression variability on image texture feat...
A method for spatial interpretation of weakly supervised deep learning models in computational pathology.
Scientific reports
Jun 5, 2025
Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typically applied for tasks where labels only exist on the patient or WSI level (e.g. patient outcomes or...
Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning.
Scientific reports
Jun 5, 2025
The pancreas is a gland in the abdomen that helps to produce hormones and digest food. The irregular development of tissues in the pancreas is termed as pancreatic cancer. Identification of pancreatic tumors early is significant for enhancing surviva...
Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography (CAIFE), an international multicentre multidisciplinary study.
BMJ open
Jun 5, 2025
INTRODUCTION: Congenital heart defect (CHD) is a significant, rapidly emerging global problem in child health and a leading cause of neonatal and childhood death. Prenatal detection of CHDs with the help of ultrasound allows better perinatal manageme...
Epistasis regulates genetic control of cardiac hypertrophy.
Nature cardiovascular research
Jun 5, 2025
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...
Humans
Induced Pluripotent Stem Cells
Connectin
Myocytes, Cardiac
Male
Heart Failure
Genome-Wide Association Study
Hypertrophy, Left Ventricular
Phenotype
Middle Aged
Magnetic Resonance Imaging
Gene Regulatory Networks
Ventricular Remodeling
Epistasis, Genetic
Female
Deep Learning
Receptor, IGF Type 1
Genetic Predisposition to Disease
Aged
Adaptive network steganography using deep learning and multimedia video analysis for enhanced security and fidelity.
PloS one
Jun 5, 2025
This study presents an advanced adaptive network steganography paradigm that integrates deep learning methodologies with multimedia video analysis to enhance the universality and security of network steganography practices. The proposed approach util...
Preoperative Identification of Papillary Thyroid Carcinoma Subtypes and Lymph Node Metastasis via Deep Learning-Assisted Surface-Enhanced Raman Spectroscopy.
ACS nano
Jun 4, 2025
Accurate preoperative diagnosis of papillary thyroid carcinoma (PTC) histological subtypes and lymph node metastasis is essential for formulating personalized treatment strategies. However, their preoperative diagnosis is challenged by the limited re...
Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.
Proceedings of the National Academy of Sciences of the United States of America
Jun 4, 2025
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...
Advancing blood cell detection and classification: performance evaluation of modern deep learning models.
BMC medical informatics and decision making
Jun 4, 2025
The detection and classification of blood cells are important in diagnosing and monitoring a variety of blood-related illnesses, such as anemia, leukemia, and infection, all of which may cause significant mortality. Accurate blood cell identification...
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