Artificial Intelligence in Medical Sensors for Clinical Decisions

Haick, Hossam; Tang, Ning

doi:10.1021/acsnano.1c00085

Cited by 111 publications

(75 citation statements)

References 88 publications

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“…The examples described above, together with other achievements of AI-supplemented sensing, suggest the beginning of a revolutionary era of intelligent biosensors, extensively discussed in literature (see Refs. [129,[141][142][143][144] for instance). Seemingly, metastructures and metasurfaces will play an important role in the development of those ideas.…”

Section: Chemical and Biological Sensingmentioning

confidence: 99%

Intelligent metaphotonics empowered by machine learning

Krasikov,

Tranter,

Bogdanov

et al. 2021

Preprint

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In the recent years, we observe a dramatic boost of research in photonics empowered by the concepts of machine learning and artificial intelligence. The corresponding photonic systems, to which this new methodology is applied, can range from traditional optical waveguides to nanoantennas and metasurfaces, and these novel approaches underpin the fundamental principles of light-matter interaction developed for a smart design of intelligent photonic devices. Concepts and approaches of artificial intelligence and machine learning penetrate rapidly into the fundamental physics of light, and they provide effective tools for the study of the field of metaphotonics driven by opticallyinduced electric and magnetic resonances. Here, we introduce this new field with its application to metaphotonics and also present a summary of the basic concepts of machine learning with some specific examples developed and demonstrated for metasystems and metasurfaces.

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Section: Chemical and Biological Sensingmentioning

confidence: 99%

Intelligent metaphotonics empowered by machine learning

Krasikov,

Tranter,

Bogdanov

et al. 2021

Preprint

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“…[22][23][24] With the emergence of flexible electronics, smart wound dressings integrating multiple sensors have been developed to detect various physiological and biochemical changes in the microenvironment of a wound site, including temperature, [25,26] pH, [27,28] glucose, [29] and other metabolites. [30][31][32] These wearable devices enable continuous point-of-care wound monitoring, [33,34] leading for a better management of the would assessement, as compared to traditional appraoches based on a visual evaluation of the bed color, which requires removal of the wound dressing beforehand. [2,35] Recent developments of smart wound dressings for real-time monitoring and controllable drug delivery have been reported.…”

Section: Introductionmentioning

confidence: 99%

Highly Efficient Self‐Healing Multifunctional Dressing with Antibacterial Activity for Sutureless Wound Closure and Infected Wound Monitoring

et al. 2021

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A common auxiliary method in wound management is the closure step, viz. the restoration of the skin function through reconnecting the wounded tissues. [4] Medical sutures and staples are the most commonly used approaches when joining wound edges. [5] However, these methods are highly invasive and can have detrimental consequences on the surrounding tissues. [6,7] In addition, these methods require professional skills and equipment, limiting their general use outside the hospital. [8] Alternative tissue connecting techniques such as Zipline, a minimal/ noninvasive wound closure device, have been investigated and publicized. [9] Nevertheless, these treatments keep the wound exposed to the environment, resulting in an increased risk of infection, and hindering wound healing. [10] Gauzes, cotton wools, and bandages that are commonly used to close wounds by wrapping or pressing are unreliable and ineffective when treating large injuries. [11,12] Therefore, there is an urgent need for multipurpose materials that combine noninvasive wound closure and dressing functions that can promote healing.Inspired by living systems, several materials with promising self-healing ability have been designed and synthesized for Wound healing represents a major clinical and public healthcare problem that is frequently challenged by infection risks, detrimental consequences on the surrounding tissues, and difficulties to monitor the healing process.Here we report on a novel self-healing, antibacterial, and multifunctional wound dressing for sutureless wound closure and real-time monitoring of the healing parameters. The self-healing elastomer contains cetyltrimethylammonium bromide (CTAB) and has high mechanical toughness (35 MJ m −3 ), biocompatibility, and outstanding antibacterial activity (bactericidal rate is ≈90% in 12 h), enabling the wound dressing to effectively inhibit bacterial growth and accelerate infected wound healing. In vivo tests based on full-thickness skin incision model shows that the multifunctional wound dressing can help in contracting wound edges and facilitate wound closure and healing, as could be evidenced by notably dense and well-organized collagen deposition. The test provides an evidence that the integrated sensor array within the multifunctional wound dressing can monitor temperature, pH, and glucose level of the wound area in real-time, providing reliable and timely information of the condition of the wound. Ultimately, the reported multifunctional dressing would be of high value in managing the burden associated with wound healing via personalised monitoring and treatment approaches, digital and other people-centred solutions for health care.

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“…For this transformation to be successful, it requires, nevertheless, a cross-disciplinary research and development and should be driven by two main factors. [20,21] The first is a shift to disease prevention and personalized medical care: Early diagnosis, together with disease prevention, is now considered a more cost-effective approach to obtain better health outcomes, as well as improving the patient's quality of life. [22,23] The principle of preventive medicine includes: prevention of disease before it occurs (primary prevention) and reducing the intensity of a disease that has already arisen, thereby controlling progression or preventing relapse after recovery (secondary prevention).…”

Section: Introductionmentioning

confidence: 99%

Smart Materials Enabled with Artificial Intelligence for Healthcare Wearables

Zheng

Tang

Omar

et al. 2021

Adv Funct Materials

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Contemporary medicine suffers from many shortcomings in terms of successful disease diagnosis and treatment, both of which rely on detection capacity and timing. The lack of effective, reliable, and affordable detection and real-time monitoring limits the affordability of timely diagnosis and treatment. A new frontier that overcomes these challenges relies on smart health monitoring systems that combine wearable sensors and an analytical modulus. This review presents the latest advances in smart materials for the development of multifunctional wearable sensors while providing a bird's eye-view of their characteristics, functions, and applications. The review also presents the state-of-the-art on wearables fitted with artificial intelligence (AI) and support systems for clinical decision in early detection and accurate diagnosis of disorders. The ongoing challenges and future prospects for providing personal healthcare with AI-assisted support systems relating to clinical decisions are presented and discussed.

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Artificial Intelligence in Medical Sensors for Clinical Decisions

Cited by 111 publications

References 88 publications

Intelligent metaphotonics empowered by machine learning

Intelligent metaphotonics empowered by machine learning

Highly Efficient Self‐Healing Multifunctional Dressing with Antibacterial Activity for Sutureless Wound Closure and Infected Wound Monitoring

Smart Materials Enabled with Artificial Intelligence for Healthcare Wearables

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