Basic Concepts of Artificial Intelligence: Primed for Clinicians

Lidströmer, Niklas; Aresu, Federica; Ashrafian, Hutan

doi:10.1007/978-3-030-64573-1_1

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…When patients receive fast instructions on how to use an inhaler and reminders to take prescription medications as prescribed, they are better able to stick to their regimens. The decrease in emergency department visits, hospital admissions, and asthma episodes that followed is proof of the efficiency of these devices (12).…”

Section: Introductionmentioning

confidence: 92%

“…Healthcare professionals are now better equipped to decide whether to modify a patient's therapy or implement interventions thanks to these insights, which range from adherence habits to environmental triggers. This abundance of data also makes it possible to spot patterns, catalysts, and connections that may otherwise go overlooked (12). IoT-enabled smart inhalers provide a variety of unique characteristics in comparison to conventional inhalers.…”

Section: Technology Overview Of Iot and Smart Inhalersmentioning

confidence: 99%

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Smart Inhalers: Harnessing Iot for Precise Asthma Management

Rakesh Margam

2024

ierj

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Effective management techniques are required for the widespread chronic respiratory disease known as asthma in order to reduce its negative effects on public health. Smart inhalers are a prime example of how the introduction of Internet of Things (IoT) technology has sparked creative solutions. In this essay, the seamless integration of IoT technology is used to elaborate on the transformational potential of smart inhalers in improving asthma management. The traditional approach to managing asthma relies on individualised prescription regimens that must be consistently followed. But obstacles including patient forgetfulness and insufficient real-time monitoring frequently prevent effective adherence, aggravating symptoms and lowering quality of life. Smart inhalers are the result of the confluence of IoT technology with asthma therapy, signalling a paradigm change. Smart inhalers, driven by IoT, offer a wide range of characteristics and signal a paradigm change in the treatment of asthma. (1) These gadgets can monitor medicine use, inhaler technique, and environmental triggers in real time since they include sensors and connection. Personalised therapy modifications are made possible by the real-time data creation that gives healthcare professionals insights into patient behaviour, adherence trends, and symptom development. The ability of smart inhalers to revolutionise medication adherence is one of their main benefits. (2)Patients are better able to maintain their regimens when they receive prompt guidance on how to use an inhaler and reminders to take prescription drugs as directed. The resultant decline in emergency room visits, hospital admissions, and asthma attacks is evidence of these devices' effectiveness. Healthcare professionals are empowered to quickly react and prevent the progression of symptoms thanks to the real-time data stream from smart inhalers. (3)Asthma care has advanced dramatically with the introduction of IoT-enabled smart inhalers, which are expected to improve asthma sufferers' medication compliance, symptom management, and overall quality of life. Predicted developments in smart inhaler technology, including artificial intelligence and predictive analytics, portend improved personalisation and therapeutic efficacy as the IoT environment changes. The promise of smart inhalers to reshape asthma care resonates deeply with the principles of patient education, engagement, and interdisciplinary collaboration among healthcare professionals, researchers, and technology developers, setting a promising trajectory for respiratory healthcare. (4)

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Section: Introductionmentioning

confidence: 92%

Section: Technology Overview Of Iot and Smart Inhalersmentioning

confidence: 99%

Smart Inhalers: Harnessing Iot for Precise Asthma Management

Rakesh Margam

2024

ierj

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“…ML is a computational model that learns from data without explicitly programming the data [ 24 ] and can be further divided into supervised, unsupervised, and reinforcement learning [ 26 ]. In supervised learning, the machine undergoes training with labeled data, making it well-suited for tasks involving regression and classification problems [ 27 ]. In contrast, unsupervised learning is designed to automatically identify patterns within unlabeled datasets [ 28 ], with its primary utility lying in the extraction of features [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study

Hennrich,

Ritz,

Hofmann

et al. 2024

BMC Health Serv Res

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Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications’ potential.We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC.Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery.We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.

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“…In addition, touch screens and tangible hardware can facilitate the use of the web, online games, and virtual worlds to improve social learning skills ( 28 ). Virtual reality applications, for example, offer autistic individuals the opportunity to improve their cognitive and social skills through safe and realistic situations, while computer, tablet, or mobile applications can be promising training tools as long as accompanied by human assistance ( 29 , 30 ). Current research has also shown that virtual reality interventions lead to faster and more stable acquisition of social skills over time ( 31 ).…”

Section: Introductionmentioning

confidence: 99%

Information and communication technologies-based interventions for children with autism spectrum conditions: a systematic review of randomized control trials from a positive technology perspective

et al. 2023

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Information and communication technologies (ICTs) have become more widely used in the past years to help people with autism spectrum conditions (ASC). Serious games embedded into computers or tablets, as well as social robots, are the most employed ICT-related tools that are appealing to and appropriate for autistic children. The goal of ICT applications is to enhance behavioral abnormalities associated with ASC while also creating an interactive link between one person and one computer. Comparatively, to human-based therapy, ICT tools aid to inspire autistic children by providing predictability and regularity of tasks. Regaining social skills is the primary behavioral goal for which ICT tools have been designed and implemented. In the past several years, many studies have been created to show how effective it is at improving targeted behaviors. However, only a small number of researchers have used an RCT approach to evaluate its effectiveness. In this systematic review, we only included RCT studies where ICT technologies were used to help children with ASC in improving their social skills. Only 14 RCT studies satisfied the criteria and 12 described significant improvements, showing how the use of technology in educational contexts produced better improvement in developing several social skill facets with respect to the traditional face-to-face approach. Some studies used interventions and outcome measures focused on the core ASC symptoms, but many others addressed neurocognitive functions directly, like social cognition or emotional regulation, while other more general functions such as language or adaptive behaviors. We propose a classification based on processes and outcome measures to foster future research in this specific area of research. The behavioral intervention mediated by technological tools such as computer-based, tablet, and social robotics, undoubtedly provides a comfortable environment that promotes constant learning for people with ASC. Evidence provided in this review highlights the translational potential of this field of study in primary care practice and educational settings.

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Basic Concepts of Artificial Intelligence: Primed for Clinicians

Cited by 5 publications

References 4 publications

Smart Inhalers: Harnessing Iot for Precise Asthma Management

Smart Inhalers: Harnessing Iot for Precise Asthma Management

Capturing artificial intelligence applications’ value proposition in healthcare – a qualitative research study

Information and communication technologies-based interventions for children with autism spectrum conditions: a systematic review of randomized control trials from a positive technology perspective

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