Automated ischemic acute infarction detection using pre-trained CNN models' deep features
B Tasci - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Background Cerebrovascular Diseases (CVD) constitute more than 50% of
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?
A Hibi, M Jaberipour, MD Cusimano, A Bilbily… - Medicine, 2022 - journals.lww.com
Background: The purpose of this study was to conduct a systematic review for understanding
the availability and limitations of artificial intelligence (AI) approaches that could …
the availability and limitations of artificial intelligence (AI) approaches that could …
Optimizing CNN‐LSTM hybrid classifier using HCA for biomedical image classification
In medical science, imaging is the most effective diagnostic and therapeutic tool. Almost all
modalities have transitioned to direct digital capture devices, which have emerged as a …
modalities have transitioned to direct digital capture devices, which have emerged as a …
A deep learning assisted image-guided framework for differentiation among tumors and hemorrhages in head imaging
Image-guided intervention refers to the analysis of multimodal data using Computer-Aided
Diagnostic (CAD) systems. The inclusion of the Deep Learning algorithms in the CAD …
Diagnostic (CAD) systems. The inclusion of the Deep Learning algorithms in the CAD …
Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable AI.
The prompt spread of COVID-19 has emphasized the necessity for effective and precise
diagnostic tools. In this article, a hybrid approach in terms of datasets as well as the …
diagnostic tools. In this article, a hybrid approach in terms of datasets as well as the …
Exploring Deep Learning and Machine Learning Approaches for Brain Hemorrhage Detection
Brain hemorrhage refers to a potentially fatal medical disorder that affects millions of
individuals. The percentage of patients who survive can be significantly raised with the …
individuals. The percentage of patients who survive can be significantly raised with the …
Framework for Healthy/Hemorrhagic Brain Condition Detection using CT Scan Images
In human physiology, the brain plays a significant role as the control center of all regulatory
processes. Any abnormality in the brain could lead to various physiological and …
processes. Any abnormality in the brain could lead to various physiological and …
Derin Öğrenme Yöntemleri Kullanılarak BT Taramalarında Beyin Kanaması Teşhisinin Karşılaştırmalı Bir Analizi
With the development of technology, artificial intelligence-based applications are used for
support in many areas. The health sector is one of the areas where such applications are …
support in many areas. The health sector is one of the areas where such applications are …
Machine Learning Applications in Traumatic Brain Injury Diagnosis and Prognosis: A Spotlight on Mild TBI and CT Imaging
Traumatic Brain Injury (TBI) poses a significant global public health challenge, contributing
to high morbidity and mortality rates and placing a substantial economic burden on …
to high morbidity and mortality rates and placing a substantial economic burden on …
Generative Intelligence‐Based Federated Learning Model for Brain Tumor Classification in Smart Health
N Maiti, R Chawla, A Quraishi, M Soni… - … for Biomedical and …, 2025 - Wiley Online Library
This study presents a sophisticated ResNet‐10 convolutional neural network model that is
specifically developed to address the classification difficulties of brain computed tomography …
specifically developed to address the classification difficulties of brain computed tomography …