Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review
BM de Vries, GJC Zwezerijnen, GL Burchell… - Frontiers in …, 2023 - frontiersin.org
Rational Deep learning (DL) has demonstrated a remarkable performance in diagnostic
imaging for various diseases and modalities and therefore has a high potential to be used …
imaging for various diseases and modalities and therefore has a high potential to be used …
A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022
KC Santosh, D GhoshRoy, S Nakarmi - Healthcare, 2023 - mdpi.com
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
Investigating ChatGPT and cybersecurity: A perspective on topic modeling and sentiment analysis
Abstract In early 2023, the Artificial Intelligence (AI) industry experienced a significant
advancement with the emergence of OpenAI's ChatGPT, a research product that …
advancement with the emergence of OpenAI's ChatGPT, a research product that …
Transfer learning approach to IDS on cloud IoT devices using optimized CNN
Data centralization can potentially increase Internet of Things (IoT) usage. The trend is to
move IoT devices to a centralized server with higher memory capacity and a more robust …
move IoT devices to a centralized server with higher memory capacity and a more robust …
A skin cancer classification approach using gan and roi-based attention mechanism
Skin cancer is a complex public health problem and one of the most common types of
cancer worldwide. A biopsy of the skin lesion gives the definitive diagnosis of skin cancer …
cancer worldwide. A biopsy of the skin lesion gives the definitive diagnosis of skin cancer …
MCLSG: Multi-modal classification of lung disease and severity grading framework using consolidated feature engineering mechanisms
AMQ Farhan, S Yang, AQS Al-Malahi… - … Signal Processing and …, 2023 - Elsevier
Human disease detection using medical images with algorithmic severity prediction is
unexplored. Deep learning algorithms for disease identification and classification from …
unexplored. Deep learning algorithms for disease identification and classification from …
Recommender system for the efficient treatment of COVID-19 using a convolutional neural network model and image similarity
Background: Hospitals face a significant problem meeting patients' medical needs during
epidemics, especially when the number of patients increases rapidly, as seen during the …
epidemics, especially when the number of patients increases rapidly, as seen during the …
[PDF][PDF] Early Detection of Alzheimer's Disease Based on Laplacian Re-Decomposition and XGBoosting.
H Ahmed, H Soliman, S El-Sappagh… - … Systems Science & …, 2023 - researchgate.net
The precise diagnosis of Alzheimer's disease is critical for patient treatment, especially at the
early stage, because awareness of the severity and progression risks lets patients take …
early stage, because awareness of the severity and progression risks lets patients take …
Classification of IHC images of NATs with ResNet-FRP-LSTM for predicting survival rates of rectal cancer patients
Background: Over a decade, tissues dissected adjacent to primary tumors have been
considered “normal” or healthy samples (NATs). However, NATs have recently been …
considered “normal” or healthy samples (NATs). However, NATs have recently been …
Detection of COVID‐19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods
Since the first case of COVID‐19 was reported in December 2019, many studies have been
carried out on artificial intelligence for the rapid diagnosis of the disease to support health …
carried out on artificial intelligence for the rapid diagnosis of the disease to support health …