Practical AI for Healthcare Professionals

Suri, Abhinav

doi:10.1007/978-1-4842-7780-5

Cited by 2 publications

(1 citation statement)

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“…22 DermAssist, a Google Health AI program, offers a similar service, but its effectiveness is yet to be fully evaluated, and concerns exist regarding the diversity of its dataset. 54 Other AI programs like Proscia DermAI, SkinVision, and Skin Image Search (SIS) also aim to assist in dermatological diagnosis, but they face challenges in achieving accurate results, Table 2 shows that 70% of the programs that were identified in this review had no data reported on their use in dermatology, specifically in SOC. Clinicians and the general public should be cautious about the use of these AI technologies until researchbased conclusions are determined.…”

Section: Current Ai Programs In Usementioning

confidence: 99%

Artificial intelligence in dermatology: advancements and challenges in skin of color

Fliorent,

Fardman,

Podwojniak

et al. 2024

Int J Dermatology

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Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human‐like problem‐solving and decision‐making. AI programs have recently acquired widespread popularity in the field of dermatology through the application of online tools in the assessment, diagnosis, and treatment of skin conditions. A literature review was conducted using PubMed and Google Scholar analyzing recent literature (from the last 10 years through October 2023) to evaluate current AI programs in use for dermatologic purposes, identifying challenges in this technology when applied to skin of color (SOC), and proposing future steps to enhance the role of AI in dermatologic practice. Challenges surrounding AI and its application to SOC stem from the underrepresentation of SOC in datasets and issues with image quality and standardization. With these existing issues, current AI programs inevitably do worse at identifying lesions in SOC. Additionally, only 30% of the programs identified in this review had data reported on their use in dermatology, specifically in SOC. Significant development of these applications is required for the accurate depiction of darker skin tone images in datasets. More research is warranted in the future to better understand the efficacy of AI in aiding diagnosis and treatment options for SOC patients.

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Section: Current Ai Programs In Usementioning

confidence: 99%

Artificial intelligence in dermatology: advancements and challenges in skin of color

Fliorent,

Fardman,

Podwojniak

et al. 2024

Int J Dermatology

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Multistep terminal guidance algorithm with intelligent adaptation to wind disturbances

Клишин

Kolesnikova

2023

EJSI

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The paper presents a qualitatively new approach to terminal guidance at the final trajectory section for the surface-to-surface class aerial vehicles. The proposed structure of the adaptive control system for an aerial vehicle is based on the multi-step terminal guidance algorithm. Adaptive corrections to the control coefficients were calculated using the developed method for identifying the wind disturbances based on the machine learning models. The work describes technique to form an intelligent algorithm for identifying intensity and direction of the wind load acting on the aerial vehicle in flight. Options of the machine learning models used in the guidance system intelligent block were investigated; their operation results are presented; and the comparative analysis has been carried out. The adaptive guidance system operation procedure is demonstrated on a typical model of the aerial vehicle flying in the atmosphere and targeting a fixed object. Numerical simulation results are presented, and possibility of using such an algorithm and implementing the described system are demonstrated.

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Practical AI for Healthcare Professionals

Cited by 2 publications

References 0 publications

Artificial intelligence in dermatology: advancements and challenges in skin of color

Artificial intelligence in dermatology: advancements and challenges in skin of color

Multistep terminal guidance algorithm with intelligent adaptation to wind disturbances

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