Survey on big data analytics in health care
Massive amount of data in different forms need to be handled in any healthcare applications.
Type of data, size of data, data security and other features has more significance in handling …
Type of data, size of data, data security and other features has more significance in handling …
Barriers and facilitators of artificial intelligence conception and implementation for breast imaging diagnosis in clinical practice: a scoping review
B Lokaj, MT Pugliese, K Kinkel, C Lovis, J Schmid - European radiology, 2024 - Springer
Objective Although artificial intelligence (AI) has demonstrated promise in enhancing breast
cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various …
cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various …
BreastDM: A DCE-MRI dataset for breast tumor image segmentation and classification
X Zhao, Y Liao, J Xie, X He, S Zhang, G Wang… - Computers in Biology …, 2023 - Elsevier
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has shown high
sensitivity to diagnose breast cancer. However, few computer-aided algorithms focus on …
sensitivity to diagnose breast cancer. However, few computer-aided algorithms focus on …
Federated learning aided breast cancer detection with intelligent Heuristic-based deep learning framework
Breast cancer is the second largest cause of female cancer death and one of the most
hazardous diseases that leads to a higher mortality rate. One of the eminent medical …
hazardous diseases that leads to a higher mortality rate. One of the eminent medical …
A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis
Objective We present the implementation and application of a case-based reasoning (CBR)
system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer …
system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer …
Discovery and clinical decision support for personalized healthcare
J Yoon, C Davtyan… - IEEE journal of biomedical …, 2016 - ieeexplore.ieee.org
With the advent of electronic health records, more data are continuously collected for
individual patients, and more data are available for review from past patients. Despite this, it …
individual patients, and more data are available for review from past patients. Despite this, it …
Blockchain-enabled contextual online learning under local differential privacy for coronary heart disease diagnosis in mobile edge computing
Due to the increasing medical data for coronary heart disease (CHD) diagnosis, how to
assist doctors to make proper clinical diagnosis has attracted considerable attention …
assist doctors to make proper clinical diagnosis has attracted considerable attention …
Reinforcement learning for personalization: A systematic literature review
The major application areas of reinforcement learning (RL) have traditionally been game
playing and continuous control. In recent years, however, RL has been increasingly applied …
playing and continuous control. In recent years, however, RL has been increasingly applied …
A clinical decision support framework for heterogeneous data sources
To keep pace with the developments in medical informatics, health medical data is being
collected continually. But, owing to the diversity of its categories and sources, medical data …
collected continually. But, owing to the diversity of its categories and sources, medical data …
A latent batch-constrained deep reinforcement learning approach for precision dosing clinical decision support
Precise prescription of medication dosing is crucial to patients, especially among Intensive
Care Unit (ICU) patients. However, improper administration of some sensitive therapeutic …
Care Unit (ICU) patients. However, improper administration of some sensitive therapeutic …