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Novel Insights into the Use of Artificial Intelligence in Clinical Medicine

A special issue of Journal of Clinical Medicine (ISSN 2077-0383).

Deadline for manuscript submissions: 20 February 2027 | Viewed by 1087

Editors


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Guest Editor
Department of Vascular and Endovascular Surgery, VA Loma Linda Healthcare System, Loma Linda, CA, USA
Interests: vascular surgery; predictive modeling; precision medicine; deep learning

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Guest Editor
Department of Radiology and Radiation Oncology, VA Long Beach Healthcare, Long Beach, CA, USA
Interests: interventional radiology; artificial intelligence; vascular Imaging; digital health technology; endovascular procedures

Special Issue Information

Dear Colleagues,

While artificial intelligence has revolutionized most aspects of our lives, the application of AI in healthcare remains in its infancy. In the era of "big data" with EMR use and the vast volume of genetic and imaging data, AI may be the next technological medium to amalgamate the vastly different forms of data points to develop faster, more accurate diagnoses, earlier risk stratification, personalized therapies, and improved operational efficiency.  In this Special Issue, we explore the novel application of AI in clinical medicine for disease predictive models, wearable technology, surgical innovation, molecular targeting, and big data science. AI is here, and as physicians, we need to harness the power of AI for our patients. As we work through the good, the bad, and the ugly of AI, I hope we can work together to harness the power of AI for our patients. Please enjoy this issue, and I hope to hear from all of you on how AI has influenced your clinical practice and research.

Dr. Sharon C. Kiang
Dr. Roger T. Tomihama
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.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

  • artificial intelligence
  • disease predictive models
  • wearable technology
  • surgical innovation
  • molecular targeting
  • big data science
  • machine learning
  • deep learning

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Published Papers (1 paper)

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Research

15 pages, 2218 KB  
Article
Frequency-Dependent Amplification of Head Motion in Infant Rockers: A Segmental IMU-Based Signal Analysis
by Alina Głowińska and Sebastian Glowinski
J. Clin. Med. 2025, 14(23), 8301; https://doi.org/10.3390/jcm14238301 - 22 Nov 2025
Cited by 2 | Viewed by 731
Abstract
(1) Background: Passive rocking is commonly used to calm infants, yet its biomechanical impact on different body segments—particularly dynamic loading of the head and torso—remains insufficiently understood. (2) Methods: An infant doll was instrumented with IMUs placed on the head, abdomen, and gluteal [...] Read more.
(1) Background: Passive rocking is commonly used to calm infants, yet its biomechanical impact on different body segments—particularly dynamic loading of the head and torso—remains insufficiently understood. (2) Methods: An infant doll was instrumented with IMUs placed on the head, abdomen, and gluteal region and subjected to controlled rocking in a standard infant rocker. Segmental responses were quantified using angular displacement, velocity, and acceleration, along with time–frequency analyses including wavelet transforms and inter-segmental transfer functions. (3) Results: The head showed the highest angular displacements and peak accelerations, predominantly in the sagittal plane, with pronounced oscillations in the 10–12 Hz range. The abdomen acted as a transitional damping zone, while the gluteal region remained largely static, serving as the mechanical input point. Frequency-domain results revealed upward amplification of motion energy, suggesting inertial and potentially resonant effects that intensify loads at the head. (4) Conclusions: Although base-level motion appears gentle, signal-level analysis reveals significant dynamic amplification toward the head. These findings underscore the importance of considering frequency-dependent transmission and segmental dynamics in infant rocker design, with implications for ergonomic safety, particularly in the early stages of development. Full article
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