Artificial intelligence in healthcare: review, ethics, trust challenges & future research directions
The use of artificial intelligence (AI) in medicine is beginning to alter current procedures in
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
prevention, diagnosis, treatment, amelioration, cure of disease and other physical and …
[HTML][HTML] Deep learning for chest X-ray analysis: A survey
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …
image analysis tasks. As the most commonly performed radiological exam, chest …
Comparison of chest radiograph interpretations by artificial intelligence algorithm vs radiology residents
Importance Chest radiography is the most common diagnostic imaging examination
performed in emergency departments (EDs). Augmenting clinicians with automated …
performed in emergency departments (EDs). Augmenting clinicians with automated …
Segmentation and classification on chest radiography: a systematic survey
T Agrawal, P Choudhary - The Visual Computer, 2023 - Springer
Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …
to medical imaging, their applications increased significantly to become a trend. Likewise …
Machine learning and artificial intelligence in the service of medicine: Necessity or potentiality?
T Alsuliman, D Humaidan, L Sliman - Current research in translational …, 2020 - Elsevier
Motivation As a result of the worldwide health care system digitalization trend, the produced
healthcare data is estimated to reach as much as 2314 Exabytes of new data generated in …
healthcare data is estimated to reach as much as 2314 Exabytes of new data generated in …
A review on electronic health record text-mining for biomedical name entity recognition in healthcare domain
Biomedical-named entity recognition (bNER) is critical in biomedical informatics. It identifies
biomedical entities with special meanings, such as people, places, and organizations, as …
biomedical entities with special meanings, such as people, places, and organizations, as …
Deep learning applied to automatic disease detection using chest x‐rays
DA Moses - Journal of Medical Imaging and Radiation …, 2021 - Wiley Online Library
Deep learning (DL) has shown rapid advancement and considerable promise when applied
to the automatic detection of diseases using CXRs. This is important given the widespread …
to the automatic detection of diseases using CXRs. This is important given the widespread …
A novel augmented deep transfer learning for classification of COVID-19 and other thoracic diseases from X-rays
Deep learning has provided numerous breakthroughs in natural imaging tasks. However, its
successful application to medical images is severely handicapped with the limited amount of …
successful application to medical images is severely handicapped with the limited amount of …
[HTML][HTML] A review on detection of pneumonia in chest X-ray images using neural networks
The health organisation has suffered from the lack of diagnosis support systems and
physicians in India. Further, the physicians are struggling to treat many patients, and the …
physicians in India. Further, the physicians are struggling to treat many patients, and the …