The use of noninvasive imaging techniques in the diagnosis of melanoma: a prospective diagnostic accuracy study

MacLellan, Alexander Nikolas; Price, Emma L.; Publicover-Brouwer, Pamela; Matheson, Kara; Ly, Thai Yen; Pasternak, Sylvia; Walsh, Noreen; Gallant, Christopher; Oakley, Amanda; Hull, Peter; Langley, Richard

doi:10.1016/j.jaad.2020.04.019

Cited by 43 publications

(39 citation statements)

References 16 publications

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“…Though some automated tools may assist with diagnosis, many have poor specificity and there is insufficient evidence for their safety and efficacy in clinical practice at this stage. [26][27][28][29][30] Therefore, the Australian melanoma guidelines do not recommend routine use of automated diagnostic tools. 14 It is anticipated that, as these tools improve, particularly with integration of artificial intelligence, the evidence for their use will strengthen.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic tools used for melanoma: A survey of Australian general practitioners and dermatologists

Nguyen¹,

Ting

Paul³

et al. 2021

Aust J Dermatology

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Background/Objective: Diagnostic tools such as dermoscopy, sequential digital dermoscopy imaging (SDDI), total body photography (TBP) and automated diagnostic tools are available to assist in early melanoma diagnosis. The use, accessibility and barriers of dermoscopy have been well studied; however, there are few similar studies regarding SDDI, TBP and automated diagnostic tools. We aim to understand the use of these diagnostic aids amongst Australian general practitioners (GPs) and dermatologists.

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Section: Introductionmentioning

confidence: 99%

Diagnostic tools used for melanoma: A survey of Australian general practitioners and dermatologists

Nguyen¹,

Ting

Paul³

et al. 2021

Aust J Dermatology

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“…The study concluded that these tools would aid in better diagnosis but will not replace clinical decision making. 133 Deep learning algorithms achieved better diagnostic performance than pathologists in identifying malignant tumours and detecting lymph node metastases in tissue sections of women with breast cancer. 4,39 In the field of radiology too, artificial intelligence systems have been on par with, and sometimes outperformed radiologists.…”

Section: Human Versus Artificial Intelligencementioning

confidence: 99%

Artificial intelligence in dermatology and healthcare: An overview

Pai

2021

IJDVL

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Many aspects of our life are affected by technology. One of the most discussed advancements of modern technologies is artificial intelligence. It involves computational methods which in some way mimic the human thought process. Just like other branches, the medical field also has come under the ambit of artificial intelligence. Almost every field in medicine has been touched by its effect in one way or the other. Prominent among them are medical diagnosis, medical statistics, robotics, and human biology. Medical imaging is one of the foremost specialties with artificial intelligence applications, wherein deep learning methods like artificial neural networks are commonly used. artificial intelligence application in dermatology was initially restricted to the analysis of melanoma and pigmentary skin lesions, has now expanded and covers many dermatoses. Though the applications of artificial intelligenceare ever increasing, large data requirements, interpretation of data and ethical concerns are some of its limitations in the present day.

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“…Tyrime dalyvavo 184 pacientai, nustatytos 59 histopatologinės melanomos diagnozės bei 150 gerybinių odos darinių. Juos analizuojant, didžiausias jautrumas ir specifiškumas buvo pasiektas naudojant neinvazinių vaizdinių tyrimų technologijas, rekomenduojant jomis papildyti diagnostikos galimybes, o ne pakeisti gydytoją [16]. Tyrime, kuris vertino 300 vaizdų klasifikavimą į piktybinius arba gerybinius darinius, buvo nustatyta, jog patys geriausi rezultatai pasiekiami diagnozuojant ne gydytojui ar algoritmui, o derinant jų siūlomas diagnozes [17].…”

Section: Odos Vėžio Diagnostika Ir Dirbtinis Intelektasunclassified

Odos Vėžio Diagnostika Ir Dirbtinis Intelektas

Janušonytė¹

2021

Health Sciences

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Dirbtinis intelektas – plačiai diskutuojama tema su sparčiai tobulėjančiomis technologijomis, ateityje neabejotinai užimsianti svarbią vietą klinikinių būklių diagnostikoje bei sveikatos priežiūroje. Viena aktualiausių dirbtinio intelekto krypčių – konvoliucinių neuroninių tinklų algoritmai, interpretuojantys vaizdinius duomenis, todėl labiausiai šioje srityje pažengusios tos specialybės, kurių praktikoje taikoma klinikinio vaizdo analizė. Odos piktybiniai navikai yra baltaodžių populiacijoje labiausiai paplitęs vėžys, kurį anksti diagnozavus galima sėkmingai gydyti, didėja pacientų išgyvenimo tikimybė. Šioje literatūros apžvalgoje aprašomas dirbtinio intelekto taikymas dermatologijoje, pastaraisiais metais diagnozuojant piktybinius odos navikus, ypač melanomą, bei šių algoritmų pažanga, jų tikslumo palyginimas su gydytojų dermatologų rezultatais. Aprašomas pacientų požiūris bei jų įžvelgiama rizika, gydytojų dermatologų požiūris ir jų žinios apie šias technologijas. Nepaisant sparčios pažangos, dirbtinio intelekto taikymas kelia daug iššūkių dėl netobulų mokymosi duomenų rinkinių, etinių klausimų bei sunkumų, identifikuojant dirbtinio intelekto algoritmo sprendimo priėmimo seką. Nors dabartiniai algoritmai kone prilygsta dermatologų lygio rezultatams ir yra patvirtinti naudojimui Europos rinkoje, tačiau jie nepakeičia gydytojo, o yra pagalbinė odos vėžio diagnostikos priemonė. Trūksta duomenų apie tokių algoritmų taikymą ir jų įtaką sprendimų priėmimui realioje klinikinėje praktikoje, reikia daugiau tyrimų apie pacientų bei gydytojų perspektyvas bei požiūrį.

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The use of noninvasive imaging techniques in the diagnosis of melanoma: a prospective diagnostic accuracy study

Cited by 43 publications

References 16 publications

Diagnostic tools used for melanoma: A survey of Australian general practitioners and dermatologists

Diagnostic tools used for melanoma: A survey of Australian general practitioners and dermatologists

Artificial intelligence in dermatology and healthcare: An overview

Odos Vėžio Diagnostika Ir Dirbtinis Intelektas

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