Special Issue "Applications of AI and Wearable Biosensors in Precision, Personalized and Predictive Medicine"
Deadline for manuscript submissions: 31 October 2023 | Viewed by 8606
Interests: biosignal processing; biomedical image processing; artificial intelligence (neural networks, fuzzy systems, bio-inspired algorithms); (bio)sensors/transducers; e-health and telemedicine; assistive technologies
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Interests: signal processing; biomedical signal processing; machine learning; body sensor networking
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Interests: video analysis; human motion analysis with applications in medical recovery; Nature-inspired optimization algorithms; geographic information systems; image processing; image fusion; multispectral; remote sensing; biomedical images
Dear Colleagues,Today’s healthcare benefits from advances in technology to discover, diagnose, and predict diseases, which were hardly possible in the past. Genome sequencing, the diagnosis of psychosis in neonates and predicting psychological abnormalities in adulthood, the use of robots for surgery, injecting bubbles for low-hazard cancer treatment, and stimulating peripheral nerves for rehabilitation using AI and biosignal processing are only a few examples. In addition, the development of new bio- and bio-compatible sensors, together with large archives and high-performance computing, make it possible to incorporate the patient history and their multimodal data for their precise diagnosis and more accurately planning for their treatment. These advances make personalized medicine, as the major goal in current healthcare, thoroughly achievable.
Precision medicine is an approach of modern medicine that uses information about a person’s genes, proteins, or clinical information to prevent, diagnose, or treat their disease. Thus, precision medicine is an evolving healthcare branch focused on tailoring medical decisions, treatments, practices, and products to individual patients based on their genetic, environmental, lifestyle, and other factors. AI is expected to help realize the promise of precision medicine in three major areas: (1) disease prevention, (2) personalized diagnosis, and (3) personalized treatment. It is expected that AI technologies, if applied openly, fairly, robustly, and in close relation to human intelligence, will open new doors for effective and personalized healthcare worldwide. In this respect, salient topics include the AI-aided diagnosis and early detection of diseases; AI-enhanced treatment and delivery; applications of wearable and implantable biosensor technologies for precision and personalized medicine; clinical decision support with AI techniques; enhancing patient care via AI applications; radiomics and quantitative imaging; bioinformatics for more effective healthcare; and innovative AI applications for patient safety.
Another branch of research is enabled by the development of high-throughput, data-intensive biomedical research assays and technologies such as DNA sequencing, imaging protocols, and wireless health monitoring biosensors and devices, which has created a need for researchers to develop strategies for analyzing, integrating and interpreting the massive amounts of data they generate. The application of data-intensive biomedical technologies in research studies has revealed that humans vary widely at the genetic, biochemical, physiological, exposure and behavioral levels, especially with respect to disease variability and treatment responsiveness. This suggests that there is often a need to tailor or personalize, medicines to the nuanced and often unique features possessed by individual patients. This personalization often goes together with the above presented precision medicine, and seldom is any distinction made between them.
The so-called predictive medicine entails predicting the probability of disease and institutes preventive measures (by means of proteomics, cytomics or screening procedures which allow for the early detection of disease) in order to either prevent the disease altogether or significantly decrease its impact upon the patient, such as by preventing mortality or limiting morbidity. Often these preventive actions are also provided by wearable or implantable biosensors attached to the patient’s body.
These three approaches of modern medicine are parts of the so called “5P medicine”. The other “P medicines” are participatory and purpose-driven approaches. Therefore, the AI used in healthcare and big data technologies are prominent tools that help modern medicine to provide high-quality and personalized healthcare.
Prof. Dr. Hariton-Nicolae Costin
Prof. Dr. Saeid Sanei
Dr. Silviu-Ioan Bejinariu
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. Biosensors 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.
- wearable biosensors
- artificial intelligence
- biosignal and image processing
- multimodal data processing
- precision, personalized and predictive medicine
- high-performance computing