Meta Learning and the AI Learning Process

Tukra, Samyakh; Lidströmer, Niklas; Ashrafian, Hutan

doi:10.1007/978-3-030-64573-1_327

Cited by 1 publication

(3 citation statements)

References 33 publications

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“…It is an ML paradigm but not a specific model. TL could improve learning in new tasks by transferring knowledge from related tasks that have been learned [9,50,51]. This approach can increase the training rate of the model, saving time, and has been considered as a potential solution in skin disease identification [52].…”

Section: Strategies For Insufficient Melanoma Samples With Transfer L...mentioning

confidence: 99%

“…Transfer learning (TL) is a form of Meta learning [9]. It is an ML paradigm but not a specific model.…”

Section: The Application Of Ai In Melanomamentioning

confidence: 99%

“…A paradigm is a philosophy and method of doing things, which was first proposed by Kuhn in 1962 [8]. The paradigms of ML can be divided into Supervised learning, Reinforcement learning, and Meta learning [9] (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

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Recent advances of artificial intelligence in melanoma clinical practice

Lin,

Shen,

Liu

et al. 2023

Melanoma Research

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Skin melanoma is a lethal cancer. The incidence of melanoma is increasing rapidly in all regions of the world. Despite significant breakthroughs in melanoma treatment in recent years, precise diagnosis of melanoma is still a challenge in some cases. Even specialized physicians may need time and effort to make accurate judgments. As artificial intelligence (AI) technology advances into medical practice, it may bring new solutions to this problem based on its efficiency, accuracy, and speed. This paper summarizes the recent progress of AI in melanoma-related applications, including melanoma diagnosis and classification, the discovery of new medication, guiding treatment, and prognostic assessment. The paper also compares the effectiveness of various algorithms in melanoma application and suggests future research directions for AI in melanoma clinical practice.

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