Results 241 to 250 of about 274,921 (303)

Review on enhancing clinical decision support system using machine learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood   +4 more
wiley   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha   +9 more
wiley   +1 more source

Precision cotton disease detection via transformer models applied to leaf imagery. [PDF]

open access: yesFront Artif Intell
Inamdar N   +5 more
europepmc   +1 more source

Graph neural network‐based attack prediction for communication‐based train control systems

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao   +3 more
wiley   +1 more source

Superimposed CSI Feedback Assisted by Inactive Sensing Information. [PDF]

open access: yesSensors (Basel)
Zhang M   +6 more
europepmc   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma   +4 more
wiley   +1 more source

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