Evaluation of a smartphone application for diagnosis of skin diseases

Mikołajczyk, Maksym; Patrzyk, Sebastian; Nieniewski, Mariusz; Woźniacka, Anna

doi:10.5114/ada.2020.101258

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…As a result, the rate of C. acnes was significantly higher in the Acne group. From this, it was believed that even with data from web questionnaires and images taken with smartphones 35,36 , one can grasp the skin condition of the subjects, and it is possible to differentiate between the Acne group and the Non-acne group.…”

Section: Discussionmentioning

confidence: 99%

Detailed microbiome analysis of sticker-stripped surface materials of acne lesions revealed acne-relatedCutibacterium acnessubtypes: a pilot study

Shimokawa,

Funatsu,

Ohata

et al. 2023

Preprint

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Cutibacterium acnes (C. acnes)is known to play a central role in pathogenesis of acne vulgaris. It has been understood that multiple phylotypes ofC. acnesexist, with certain types being more prevalent in patient with acne vulgaris and others more common in healthy individuals. In this context, we conducted a preliminary study using self-collected samples via an adhesive sticker (MySkin®) to analyze the skin microbiome of Japanese women. The study aimed to determine the role ofC. acnesand its specific phylotypes in the development of acne vulgaris.Participants in this study were Japanese females aged between their 20s and 40s. Dermatologists evaluate the data from web-based questionnaires and smartphone image submissions to classify subjects into either the Acne or Non-acne group. Quality assessment of DNA extracted from the sticker was conducted, followed by amplification of the16S rRNAregion using PCR. Subsequent microbial community analysis was performed using next-generation sequencing techniques. Genetic classification ofC. acneswas accomplished through single locus sequence typing.Results indicated a bacterial community composition on the facial skin surface predominantly consisting ofC. acnesclusters, with over half of these clusters constituted byC. acnes. Notably, the Acne group exhibited a significantly higher proportion ofC. acnesrelative to total bacterial presence compared to the Non-acne group. Analysis ofC. acnesphylotypes revealed a markedly lower presence of type III in the Acne group (vs. Non-acne group,p<0.05). No significant differences were observed in the prevalence of Types IA1, IA2, II, and IB between the two groups. The predominant phylotypes ofC. acnesidentified were IA2_2_F0 (23.9%), IA1_4_A0 (20.6%), and II_2_K0 (18.6%). Within the Acne group, an increase in IA2_1_F1 and a decrease in III_1_L0 were observed (vs. Non-acne group, p<0.05).This study underscores the feasibility of using self-collected and mailed-in samples for qPCR and microbiome analysis, maintaining diagnostic quality comparable to in-person assessments. Furthermore, the variation in the expression ofC. acnesphylotypes across skin surfaces between acne-afflicted and healthy individuals could suggest that shifts in phylotype expression patterns may be indicative of skin susceptibilities to acne development.

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Section: Discussionmentioning

confidence: 99%

Detailed microbiome analysis of sticker-stripped surface materials of acne lesions revealed acne-relatedCutibacterium acnessubtypes: a pilot study

Shimokawa,

Funatsu,

Ohata

et al. 2023

Preprint

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“…Which of the following statements regarding new information technologies such as AI in the next 20 years seem to be most accurate to you? ever, the value of popular smartphone applications for diagnosing popular skin diseases is poorly understood [7]. Moreover, teledermatology services such as remote patient visits are of considerable significance when medical visits are not possible.…”

Section: Discussionmentioning

confidence: 99%

“…However, some scientific publications suggest that AI could be equal or even better at diagnosing skin cancers, mainly melanoma, than qualified dermatologists. However, the value of popular smartphone applications for diagnosing popular skin diseases is poorly understood [ 7 ]. Moreover, teledermatology services such as remote patient visits are of considerable significance when medical visits are not possible.…”

Section: Discussionmentioning

confidence: 99%

A study of attitudes among Polish dermatologists and dermatology trainees regarding modern technologies in medicine

Patrzyk¹,

Bielecki²,

Woźniacka³

2022

pdia

Self Cite

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Introduction: Dermatology offers great potential for the use of modern technologies such as remote online consultations, initial diagnostics via smartphone and computer applications, and artificial intelligence (AI)-based support for doctors. Aim: To investigate the attitude of dermatologists to such technologies. Material and methods: The participants completed a paper questionnaire comprising 16 questions regarding data such as age, gender and advancement in specialization, as well as views on the safety, benefits and future role of technologies such as AI and telemedicine in the future of medicine. The participants were chosen by snowball sampling. In total, 140 questionnaires were obtained; this was reduced to 90 by removing 50 respondents who were not familiar with term "telemedicine". The obtained data were subjected to statistical analysis. Results: The prevailing opinion was that while AI will not be able to replace doctors in the future, it could be used to improve the skills of medical personnel. Among the possible applications of these technologies in medicine, most of the responses indicated disease prevention (32%) and education (26%). None of the participants indicated that telemedicine could completely replace the traditional visit to the doctor's office. Conclusions: While the connection between medicine and modern technology is becoming stronger, most respondents believe that it is not possible for technologies such as AI or telemedicine to replace the work of human doctors.

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“…Along with providing assistance in data collection, IoT has a promising future in providing diagnosis applications toward end users via web-based applications [22]. For example, IoT has been reported to be used in dermatological diagnosis [23], COVID-19 symptom diagnosis [24], predicting pathological conditions of cardiovascular diseases [25], and detecting and observing diabetes patients [26]. The communication technologies used for communications in IoT-integrated devices vary; along with the traditional methods such as WiFi, Bluetooth, and Ethernet, there are many other technologies such as radio-frequency identification and near-field communication, Bluetooth Low Energy, Li-Fi, ZigBee, Z-wave, and LoRa [27].…”

Section: Introductionmentioning

confidence: 99%

Development and Performance Evaluation of an IoT-Integrated Breath Analyzer

Khamis

Idris

Abdellatif

et al. 2023

IJERPH

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Although alcohol consumption may produce effects that can be beneficial or harmful, alcohol consumption prevails among communities around the globe. Additionally, alcohol consumption patterns may be associated with several factors among communities and individuals. Numerous technologies and methods are implemented to enhance the detection and tracking of alcohol consumption, such as vehicle-integrated and wearable devices. In this paper, we present a cellular-based Internet of Things (IoT) implementation in a breath analyzer to enable data collection from multiple users via a single device. Cellular technology using hypertext transfer protocol (HTTP) was implemented as an IoT gateway. IoT integration enabled the direct retrieval of information from a database relative to the device and direct upload of data from the device onto the database. A manually developed threshold algorithm was implemented to quantify alcohol concentrations within a range from 0 to 200 mcg/100 mL breath alcohol content using electrochemical reactions in a fuel-cell sensor. Two data collections were performed: one was used for the development of the model and was split into two sets for model development and on-machine validation, and another was used as an experimental verification test. An overall accuracy of 98.16% was achieved, and relative standard deviations within the range from 1.41% to 2.69% were achieved, indicating the reliable repeatability of the results. The implication of this paper is that the developed device (an IoT-integrated breath analyzer) may provide practical assistance for healthcare representatives and researchers when conducting studies involving the detection and data collection of alcohol consumption patterns.

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Evaluation of a smartphone application for diagnosis of skin diseases

Cited by 6 publications

References 7 publications

Detailed microbiome analysis of sticker-stripped surface materials of acne lesions revealed acne-relatedCutibacterium acnessubtypes: a pilot study

Detailed microbiome analysis of sticker-stripped surface materials of acne lesions revealed acne-relatedCutibacterium acnessubtypes: a pilot study

A study of attitudes among Polish dermatologists and dermatology trainees regarding modern technologies in medicine

Development and Performance Evaluation of an IoT-Integrated Breath Analyzer

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