Advancements in Medical and Assistive Technologies Using Artificial Intelligence and Deep Learning Techniques—2nd Edition

Dear Colleagues,

This second edition of “Advancements in Medical and Assistive Technologies Using Artificial Intelligence and Deep Learning Techniques" https://www.mdpi.com/journal/technologies/special_issues/62L241LE6H aims to build on the success of the first edition, which brought together 14 high-quality contributions spanning brain tumor segmentation in MRI, EEG-based motor imagery classification, automated heart sound analysis, arrhythmia detection from ECG signals, lung and colon cancer classification from histopathological images, diabetic retinopathy grading, LLM-based chatbots for rehabilitation adherence, ethical considerations in assistive technologies, and assistive robotics. With this Special Issue we seek to further advance the integration of artificial intelligence (AI), Machine Learning (ML), and deep learning (DL) techniques into medical and assistive technology (AT).

The convergence of AI, ML, and DL with biomedical applications continues to reshape the healthcare landscape, offering unprecedented precision and efficiency in diagnosing, monitoring, and treating a wide spectrum of conditions. As the demand for personalized, accessible, and equitable healthcare grows, these technologies play a pivotal role in overcoming the limitations of traditional methods, enabling healthcare systems to process vast, heterogeneous datasets to enable more accurate and timely clinical interventions. These advancements not only refine existing medical practices but also catalyze the development of novel tools and intelligent systems that are redefining the future of patient care and assistive solutions for individuals with disabilities.

For this second edition, we aim to gather cutting-edge research at the intersection of AI, ML, DL, and biomedical engineering, with an expanded thematic scope that reflects the field’s rapidly evolving landscape. In particular, this edition places special emphasis on the following emerging areas:

• ML, DL, and AI in medical diagnostics for early disease detection and classification through biomedical imaging or signal processing.
• Novel methods, frameworks, and techniques for augmented reality, virtual reality, serious games, gamification, and telerehabilitation.
• The development of adaptive assistive technologies and robotics to support individuals with disabilities.
• Advancements in healthcare monitoring systems powered by AI for real-time analysis.
• AI-driven biomedical signal processing.
• Smart medical device innovation for improved patient care, including security for telemedicine technologies.
• The use of AI and LLM in personalized medicine for treatment plans.
• The integration of AI and LLM into IoT in healthcare environments to optimize patient outcomes.
• Federated learning, transfer learning, and other advanced learning paradigms applied to healthcare data.
• The ethical, privacy and security challenges in AI-driven healthcare systems.

This Special Issue will feature work that presents novel systems, approaches, frameworks, methods, algorithms, or applications, pushing the boundaries of what AI, ML, and DL can achieve in the healthcare sector.

We welcome original research articles, comprehensive reviews, and short communications from researchers worldwide.

Dr. Everardo Inzunza-González
Dr. Fabrizio Stasolla
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 250 words) can be sent to the Editorial Office for assessment.

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. Technologies 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 1800 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.

• artificial intelligence
• medical imaging
• machine learning
• medical image classification
• deep learning
• H-IoT
• biomedical signal processing
• deep neural networks
• CNNs
• health informatics
• computer-aided diagnosis
• data science