Results 101 to 110 of about 261,899 (291)

An artificial intelligence model for early-stage breast cancer classification from histopathological biopsy images

Frontiers in Artificial Intelligence
Accurate identification of breast cancer subtypes is essential for guiding treatment decisions and improving patient outcomes. In current clinical practice, determining histological subtypes often requires additional invasive procedures, delaying ...
Neil Chaudhary, A. Z. Dhunny
doaj   +1 more source

A 73‐Year‐Old Man With Several Years of Difficulty Climbing Stairs and Frequent Tripping

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT A 73‐year‐old man presented with progressive weakness and atrophy predominantly affecting the distal finger flexors and quadriceps muscles. Electrophysiological studies demonstrated mixed myogenic and neurogenic features. Muscle MRI showed inflammatory changes, and muscle biopsy revealed granulomatous myositis with histologic features ...
Mehmet Can Sari, Arens Taga, Sonya Ulrike Steele, Ahmet Hoke   +3 more
wiley   +1 more source

BreNet: Attention-Enhanced Multi-Scale CNN Framework for Breast Cancer Classification in Histopathological Images

IEEE Access
Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment plans.
Helala M. Alshehri
doaj   +1 more source

Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini, Alessia Casarini, Niccolò Biagioli, Laura Mirandola, Daniela Ballotta, Paul Summers, Simona Scolastico, Laura Madrassi, Maurilio Genovese, Marcella Malagoli, Gaetano Cantalupo, Giada Giovannini, Matteo Pugnaghi, Niccolò Orlandi, Laura Tassi, Valeria Cuccarini, Domenico Aquino, Elena Tartara, Fulvia Palesi, Giuseppe Didato, Paolo Vitali, the 3TLE Study Group, Roberta Di Giacomo, Fabio Doniselli, Federica Mazzi, Carlo Andrea Galimberti, Claudia A. M. Gandini Wheeler‐Kingshott, Stefano Meletti, Anna Elisabetta Vaudano   +28 more
wiley   +1 more source

Transfer Learning Fusion Approaches for Colorectal Cancer Histopathological Image Analysis

Journal of Imaging
It is well-known that accurate classification of histopathological images is essential for effective diagnosis of colorectal cancer. Our study presents three attention-based decision fusion models that combine pre-trained CNNs (Inception V3, Xception ...
Houda Saif ALGhafri, Chia S. Lim
doaj   +1 more source

Normal‐Appearing White Matter Injury Mediates Chronic Deep Venous Hypoxia and Disease Progression in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang, Huiying Wang, Zhizheng Zhuo, Ai Guo, Ke Lv, Decai Tian, Chao Chai, Yunyun Duan, Shuang Xia   +8 more
wiley   +1 more source

Classification of histopathological images for oral cancer in early stages using a deep learning approach

Journal of Intelligent Systems
Problem – Diagnosing early-stage oral squamous cell carcinoma (OSCC) is necessary for patient treatment and survival. The staining normalization and augmentation of histopathological images can play an important role in improving the accuracy of early ...
Alsaedi Raneem Y., Alsharif Hussam J.
doaj   +1 more source

Improving Cell Nuclei Segmentation in Pathological Tissues Using Self-Supervised Regression Method

IEEE Access
Digital pathology, integral to cancer diagnosis, heavily utilizes the analysis of whole slide images (WSIs) to detect cancer cells. Traditionally, WSIs are manually examined—a process that is not only time-consuming but also subject to observer ...
Hesham Ali, Mostafa Hammouda, Mustafa Elattar, Sahar Selim   +3 more
doaj   +1 more source

SPG4 and Dementia: Expanding the Clinical Spectrum

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Hereditary spastic paraplegia (HSP) is a group of disorders characterized by progressive spasticity and lower limb weakness, with mutations in SPG4/SPAST being the most common cause. Detailed studies and clinical and molecular comparisons across different populations are missing.
Emanuele Panza, Arun Meyyazhagan, Eliseo Picchi, Gustavo Ribas, Ingrid Faber, Ryosuke Miyamoto, Preethi Basavaraju, Paolo Eusebi, Haripriya Kuchi Bhotla, Mario Stasi, Fabrizio Gaudiello, Francesco Patti, Filippo Maria Santorelli, Marcondes Cavalcante França Jr, José Luiz Pedroso, Orlando Graziani Povoas Barsottini, Hélio Afonso Ghizoni Teive, Peter Henry St George‐Hyslop, Toshitaka Kawarai, Antonio Orlacchio   +19 more
wiley   +1 more source

Machine Learning Models for the Classification of Histopathological Images of Colorectal Cancer

Applied Sciences
The aim of this study was to explore the application of computational models for the analysis of histopathological images in the context of colon cancer.
Nektarios Georgiou, Pavlos Kolias, Ioanna Chouvarda   +2 more
doaj   +1 more source