Precision Medicine, AI, and the Future of Personalized Health Care

Johnson, Kevin B.; Wei, Wei‐Qi; Weeraratne, Dilhan; Frisse, Mark E.; Misulis, Karl E.; Rhee, Kyu; Zhao, Juan; Snowdon, Jane L.

doi:10.1111/cts.12884

Cited by 603 publications

(348 citation statements)

References 87 publications

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“…The defence mechanisms represented by inflammation and the activity of immune cells, even when involved in hindering a virus that is the causative agent of colds, become part of precision medicine, where prevention, diagnosis, prognosis, and treatment are focused on the target subject. Precision medicine is a part of healthcare that considers individual variability and represents an ever-developing medical approach [104,105]. In this matter, the ABO blood group system has been reported to be relevant in defining susceptibility to COVID-19 [106].…”

Section: Inflammation and Immune Response-molecular Cross-talkmentioning

confidence: 99%

How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn

Signorini

Pignatti

Coccini

2021

Life

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Inflammatory and immune processes are defensive mechanisms that aim to remove harmful agents. As a response to infections, inflammation and immune response contribute to the pathophysiological mechanisms of diseases. Coronavirus disease 2019 (COVID-19), whose underlying mechanisms remain not fully elucidated, has posed new challenges for the knowledge of pathophysiology. Chiefly, the inflammatory process and immune response appear to be unique features of COVID-19 that result in developing a hyper-inflammatory syndrome, and air pollution, the world’s largest health risk factor, may partly explain the behaviour and fate of COVID-19. Understanding the mechanisms involved in the progression of COVID-19 is of fundamental importance in order to avoid the late stage of the disease, associated with a poor prognosis. Here, the role of the inflammatory and immune mediators in COVID-19 pathophysiology is discussed.

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Section: Inflammation and Immune Response-molecular Cross-talkmentioning

confidence: 99%

How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn

Signorini

Pignatti

Coccini

2021

Life

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“…For instance, the construction of multi-material parts has opened new possibilities in combining materials to create entirely new systems that operate differently than their individual components, and may exhibit advantageous emergent behaviors. Design customization on a per-print basis opens new doors for personalized medicine, but again, there is a need for new computational approaches for automatically tuning designs to a patient’s specified needs [ 154 ]. Future advances in design are necessary to aid nonlinear and integrated decision making across materials and processes for specified applications, where there is much room to explore new methods for fully leveraging the capabilities 3D polymer printing.…”

Section: Discussionmentioning

confidence: 99%

Polymer 3D Printing Review: Materials, Process, and Design Strategies for Medical Applications

et al. 2021

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Polymer 3D printing is an emerging technology with recent research translating towards increased use in industry, particularly in medical fields. Polymer printing is advantageous because it enables printing low-cost functional parts with diverse properties and capabilities. Here, we provide a review of recent research advances for polymer 3D printing by investigating research related to materials, processes, and design strategies for medical applications. Research in materials has led to the development of polymers with advantageous characteristics for mechanics and biocompatibility, with tuning of mechanical properties achieved by altering printing process parameters. Suitable polymer printing processes include extrusion, resin, and powder 3D printing, which enable directed material deposition for the design of advantageous and customized architectures. Design strategies, such as hierarchical distribution of materials, enable balancing of conflicting properties, such as mechanical and biological needs for tissue scaffolds. Further medical applications reviewed include safety equipment, dental implants, and drug delivery systems, with findings suggesting a need for improved design methods to navigate the complex decision space enabled by 3D printing. Further research across these areas will lead to continued improvement of 3D-printed design performance that is essential for advancing frontiers across engineering and medicine.

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“…Such work could also advance the management of spinal conditions by encouraging efficiencies and innovation in clinical assessment and therapy development because the measures may detect change earlier than clinical endpoints (more sensitive) and are independent of assessor variability (more objective). Furthermore, these measures may aid in augmented intelligence-driven clinical decision making, allowing the clinician to better risk-and treatment-stratify patients using this information along with other clinical markers and endpoints 14 .…”

Section: Discussionmentioning

confidence: 99%

“…Using data-driven approaches, these complementary imaging metrics, combined with examination and imaging findings, may lead to an improved understanding of spinal disease and deliver more sensitive and specific measures of spinal pathology with greater diagnostic, prognostic, and predictive value 12,13 . Artificial intelligence combined with precision medicine approaches can enable augmented intelligence-driven medical decision making and the personalized delivery of health care 14 .…”

Section: Trmentioning

confidence: 99%

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions

Weber

Abbott

Bojilov

et al. 2021

Sci Rep

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Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-dependent manual segmentation techniques. A convolutional neural network (CNN) model was trained to segment seven cervical spine muscle groups (left and right muscles segmented separately, 14 muscles total) from Dixon MRI scans (n = 17, 17 scans < 2 weeks post motor vehicle collision (MVC), and 17 scans 12 months post MVC). The CNN MFI measures demonstrated high test reliability and accuracy in an independent testing dataset (n = 18, 9 scans < 2 weeks post MVC, and 9 scans 12 months post MVC). Using the CNN in 84 participants with scans < 2 weeks post MVC (61 females, 23 males, age = 34.2 ± 10.7 years) differences in MFI between the muscle groups and relationships between MFI and sex, age, and body mass index (BMI) were explored. Averaging across all muscles, females had significantly higher MFI than males (p = 0.026). The deep cervical muscles demonstrated significantly greater MFI than the more superficial muscles (p < 0.001), and only MFI within the deep cervical muscles was moderately correlated to age (r > 0.300, p ≤ 0.001). CNN’s allow for the accurate and rapid, quantitative assessment of the composition of the architecturally complex muscles traversing the cervical spine. Acknowledging the wider reports of MFI in cervical spine disorders and the time required to manually segment the individual muscles, this CNN may have diagnostic, prognostic, and predictive value in disorders of the cervical spine.

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Precision Medicine, AI, and the Future of Personalized Health Care

Cited by 603 publications

References 87 publications

How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn

How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn

Polymer 3D Printing Review: Materials, Process, and Design Strategies for Medical Applications

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions

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