Special Issue "Real-Time Diagnosis Algorithms in Biomedical Applications and Decision Support Tools"
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 July 2022 | Viewed by 13557
Interests: hardware implementation of algorithms; wood moisture sensing; IoT for sensor networks; hyperspectral sensing and processing
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The use of automatic support tools for the medical practice is continuously increasing. From family doctors to surgeons, specialists are using a wide number of devices, which certainly increase the level of accuracy in their diagnoses. Deep learning algorithms and data analysis in general are providing new possibilities for doctors. Many doctors now use user-friendly tools and devices in their daily practice, even though they are necessarily skilled in advanced tools or research-level algorithms.
On the other hand, many of the newly proposed biomedical algorithms require offline tools, i.e., data must be saved, processed, and, finally, a result is provided to the doctor, to be used by him as a support for patient diagnosis. This process can be followed in many occasions where the medical test is done in advance and, after some hours or days, the result is sent to the doctor. However, other common situations exist where helping the doctor immediately by providing important data on the patient is required.
Currently, it is common that medical devices provide real-time monitoring of patients by providing basic data (cardiac rhythm, blood pressure, and body temperature), but due to the algorithm complexity, it is uncommon to find real-time diagnosis since most of the algorithms require a complex computation and real-time results cannot be provided.
Artificial intelligence algorithms have proven to be tools that improve the accuracy of detection in many medical problems; they provide predictions and can learn new features while being used. However, real-time implementation is still a challenge if we consider that the results should be given in a few seconds (at most) so that they can be helpful to the practitioner. So that this goal can be achieved, special hardware as well as parallel software implementations must be developed.
This Special Issue welcomes real-time implementations of algorithms that can serve as an immediate decision-support tools in medical situations. This Special Issue is open but not restricted to any of the following biomedical areas where a real-time implementation is proposed:
- Signal processing algorithms for real-time pathology detection;
- Image processing algorithms for real-time diagnosis;
- Artificial intelligence algorithm for real-time implementation (this may include online training);
- Real-time parallel software implementations;
- Hardware implementations for computation speed-up, based on specific hardware: VLSI, FPGA, GPU, etc;
- Hardware implementations for portability and/or low power;
- User tools for real-time decision-support systems;
- Implementations for real-time remote diagnosis.
Prof. Dr. Alfredo Rosado
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