Implementation of Personalized Medicine by Artificial Intelligence Platform

Review Computer Science, Artificial Intelligence

Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research

Toufique A. Soomro et al.

Summary: This article provides an extensive review of AI-based methods for efficient COVID-19 diagnosis, covering image acquisition, segmentation, classification, and follow-up diagnosis. Research indicates that AI and machine learning technologies have enhanced the accuracy of Covid-19 diagnosis and have successfully worked with minimal data. Future studies may focus on multi-modality models and selecting optimal model architectures to introduce more intelligence to medical systems, capturing disease characteristics through learning from multi-modality data for reliable COVID-19 diagnosis and timely treatment.

ARTIFICIAL INTELLIGENCE REVIEW (2022)

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Article Computer Science, Information Systems

Dis-Cover AI Minds to Preserve Human Knowledge

Leonardo Ranaldi et al.

Summary: This article discusses some issues in modern AI technologies, including the use of learning algorithms, symbolic structures, and knowledge representation. The author proposes a new perspective that combines rules, learning, and human knowledge.

FUTURE INTERNET (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

Regulatory Issues and Challenges to Artificial Intelligence Adoption

Harlan Benjamin Harvey et al.

RADIOLOGIC CLINICS OF NORTH AMERICA (2021)

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Article Computer Science, Artificial Intelligence

Evaluating diagnostic content of AI-generated radiology reports of chest X-rays

Zaheer Babar et al.

Summary: Radiology reports play a crucial role in communication between radiologists and clinicians, and assessing the quality of AI-generated reports is challenging. Research is focusing on proposing new evaluation metrics to quantify the diagnostic content of reports and utilizing a sentence dictionary to speed up training.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

Convolutional and Recurrent Neural Networks for Physical Action Forecasting by Brain-Computer Interface

Kostiantyn Kostiukevych et al.

Summary: This study explores the classification of EEG data collected by BCI using deep neural networks, and finds that some hybrid DNNs can reliably classify physical actions. These hybrid models can be implemented with simple combinations and used on devices with limited computational resources.

PROCEEDINGS OF THE 11TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS'2021), VOL 2 (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

Deep Learning with Noise Data Augmentation and Detrended Fluctuation Analysis for Physical Action Classification by Brain-Computer Interface

Yuri Gordienko et al.

Summary: This study focuses on classifying physical actions based on EEG data gathered by BCI using a relatively small DNN. The results show that physical actions can be categorized into different groups based on complexity and feasibility of classification, with statistically reliable results obtained by the DNN. This approach could potentially be used on Edge Computing infrastructures with limited computational resources.

2021 8TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2021) (2021)

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Article Oncology