A systematic survey of computer-aided diagnosis in medicine: Past and present developments
J Yanase, E Triantaphyllou - Expert Systems with Applications, 2019 - Elsevier
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …
expended in the interface of medicine and computer science. As some CAD systems in …
Explainable artificial intelligence (XAI) in biomedicine: Making AI decisions trustworthy for physicians and patients
J Lötsch, D Kringel, A Ultsch - BioMedInformatics, 2021 - mdpi.com
The use of artificial intelligence (AI) systems in biomedical and clinical settings can disrupt
the traditional doctor–patient relationship, which is based on trust and transparency in …
the traditional doctor–patient relationship, which is based on trust and transparency in …
Survey on machine learning and deep learning applications in breast cancer diagnosis
Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …
A comprehensive review on seismocardiogram: current advancements on acquisition, annotation, and applications
In recent years, cardiovascular diseases are on the rise, and they entail enormous health
burdens on global economies. Cardiac vibrations yield a wide and rich spectrum of essential …
burdens on global economies. Cardiac vibrations yield a wide and rich spectrum of essential …
[HTML][HTML] Big data in healthcare: Conceptual network structure, key challenges and opportunities
Big data is a concept that deals with large or complex data sets by using data analysis tools
(eg, data mining, machine learning) to analyze information extracted from several sources …
(eg, data mining, machine learning) to analyze information extracted from several sources …
Disease localization and severity assessment in chest X-ray images using multi-stage superpixels classification
Abstract Background and Objectives Chest X-ray (CXR) is a non-invasive imaging modality
used in the prognosis and management of chronic lung disorders like tuberculosis (TB) …
used in the prognosis and management of chronic lung disorders like tuberculosis (TB) …
Deep learning-based computer-aided diagnosis (cad): applications for medical image datasets
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for
diagnostic prediction over the years. This article focuses on the development of an …
diagnostic prediction over the years. This article focuses on the development of an …
Classification of histopathology images of lung cancer using convolutional neural network (CNN)
N Baranwal, P Doravari… - Disruptive Developments in …, 2022 - taylorfrancis.com
Cancer is the uncontrollable cell division of abnormal cells inside the human body, which
can spread to other body organs. It is a non-communicable diseases (NCDs), which account …
can spread to other body organs. It is a non-communicable diseases (NCDs), which account …
Non-player character decision-making in computer games
MÇ Uludağlı, K Oğuz - Artificial Intelligence Review, 2023 - Springer
One of the most overlooked challenges in artificial intelligence (AI) for computer games is to
create non-player game characters (NPCs) with human-like behavior. Modern NPCs …
create non-player game characters (NPCs) with human-like behavior. Modern NPCs …
[HTML][HTML] Using feature maps to unpack the CNN 'Black box'theory with two medical datasets of different modality
Convolutional neural networks (CNNs) have been established for a comprehensive range of
computer vision problems across several benchmarks. Visualization and analysis of feature …
computer vision problems across several benchmarks. Visualization and analysis of feature …