Advancing Radiology with AI: From Algorithms to Clinical Practice
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 333
Special Issue Editors
Interests: radiodiagnostics; biomedical imaging; radiology; image analysis; radiomics; machine learning; artificial intelligence; ultrasound; computed tomography; magnetic resonance imaging; ultrasound elastography; abdominal radiology
Interests: magnetic resonance; computed tomography; artificial intelligence; radiomics; neuroradiology; MRI lymphography; medical imaging
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are delighted to invite you to contribute to the upcoming Special Issue of Bioengineering titled "Advancing Radiology with AI: From Algorithms to Clinical Practice," guest-edited by Dr. Maurizio Cè and Dr. Michaela Cellina.
The field of diagnostic imaging is undergoing a transformative shift driven by rapid advancements in artificial intelligence (AI). This Special Issue aims to highlight the cutting-edge developments, applications and future directions of AI in diagnostic imaging, showcasing its potential to revolutionize healthcare.
The Special Issue will encompass a wide range of topics, from novel AI algorithms and methodologies to their real-world applications and implications in various imaging modalities such as MRI, CT, X-rays and ultrasound. We also seek to address the challenges and ethical considerations associated with integrating AI into clinical practice
Key topics of the Special Issue include the following:
- AI Algorithms and Techniques
- From traditional machine learning to deep neural networks, this Special Issue covers the latest advancements in AI-driven diagnostic imaging applications;
- Methodological issues related to constructing robust radiomics pipelines, including image preprocessing, data augmentation, feature selection techniques, validation methods and calibration;
- Studies providing external validation of existing models to assess the real-world effectiveness and generalizability of AI-driven approaches.
- Clinical Integration and Impact
- Workflow Optimization: AI’s role in streamlining diagnostic procedures to improve efficiency and reduce time-to-diagnosis, including automated image analysis and the prioritization of critical findings.
- Decision Support Systems: AI assisting clinicians with diagnosis and treatment planning by providing evidence-based recommendations and reducing diagnostic errors, including the integration of AI tools into electronic health records (EHRs).
- Patient Outcomes: Assessing the impact of AI on diagnostic accuracy and patient care, including enhancing the early detection of diseases, personalizing treatment plans and monitoring patient progress. Studies on cost-effectiveness and patient satisfaction with AI-assisted diagnostics are also encouraged.
- Challenges and Ethical Considerations
- Data Privacy and Security: Ensuring patient confidentiality in AI applications through robust encryption, secure data storage solutions and compliance with data protection regulations.
- Bias and Fairness: Addressing biases in AI algorithms that may lead to unequal healthcare outcomes. Strategies for detecting, mitigating and preventing biases related to race, gender, socioeconomic status and other factors.
- Regulatory and Compliance Issues: Navigating the regulatory landscape to ensure that AI tools meet clinical and safety standards.
We believe your expertise and research would make a significant contribution to this Special Issue and the field of AI in radiology.
We look forward to your positive response and are excited about the possibility of featuring your work in this Special Issue. Should you have any questions or require further information, please do not hesitate to contact us.
Thank you for your consideration.
Dr. Maurizio Cè
Dr. Michaela Cellina
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- medical imaging
- radiology
- artificial intelligence
- machine learning
- deep learning
- radiomics
- radiogenomics
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