scholarly journals Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e050203
Author(s):  
Claire Felmingham ◽  
Samantha MacNamara ◽  
William Cranwell ◽  
Narelle Williams ◽  
Miki Wada ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Skin Cancer ◽  
Skin Lesions ◽  
Ethics Committee ◽  
Management Decision ◽  
Primary Analysis ◽  
Intelligence System ◽  
Cancer Management ◽  
Alfred Hospital ◽  
The Impact

IntroductionConvolutional neural networks (CNNs) can diagnose skin cancers with impressive accuracy in experimental settings, however, their performance in the real-world clinical setting, including comparison to teledermatology services, has not been validated in prospective clinical studies.Methods and analysisParticipants will be recruited from dermatology clinics at the Alfred Hospital and Skin Health Institute, Melbourne. Skin lesions will be imaged using a proprietary dermoscopic camera. The artificial intelligence (AI) algorithm, a CNN developed by MoleMap Ltd and Monash eResearch, classifies lesions as benign, malignant or uncertain. This is a preintervention/postintervention study. In the preintervention period, treating doctors are blinded to AI lesion assessment. In the postintervention period, treating doctors review the AI lesion assessment in real time, and have the opportunity to then change their diagnosis and management. Any skin lesions of concern and at least two benign lesions will be selected for imaging. Each participant’s lesions will be examined by a registrar, the treating consultant dermatologist and later by a teledermatologist. At the conclusion of the preintervention period, the safety of the AI algorithm will be evaluated in a primary analysis by measuring its sensitivity, specificity and agreement with histopathology where available, or the treating consultant dermatologists’ classification. At trial completion, AI classifications will be compared with those of the teledermatologist, registrar, treating dermatologist and histopathology. The impact of the AI algorithm on diagnostic and management decisions will be evaluated by: (1) comparing the initial management decision of the registrar with their AI-assisted decision and (2) comparing the benign to malignant ratio (for lesions biopsied) between the preintervention and postintervention periods.Ethics and disseminationHuman Research Ethics Committee (HREC) approval received from the Alfred Hospital Ethics Committee on 14 February 2019 (HREC/48865/Alfred-2018). Findings from this study will be disseminated through peer-reviewed publications, non-peer reviewed media and conferences.Trial registration numberNCT04040114.

scholarly journals Screening for Melanoma and Other Skin Cancer Shows a Higher Early Melanoma Incidence: Social Educational Program “Life Fear-Free”

2021 ◽  
Vol 8 (1) ◽  
pp. 54-68
Author(s):  
Lev Demidov ◽  
Igor Samoylenko ◽  
Nina Vand ◽  
Igor Utyashev ◽  
Irina Shubina ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Screening Program ◽  
Excisional Biopsy ◽  
Skin Lesions ◽  
Detection Methods ◽  
Non Melanoma Skin Cancer ◽  
The Social ◽  
Educational Campaign ◽  
Skin Cancer Detection ◽  
The Impact

Background: The screening program Life Fear-Free (LFF) aimed at early diagnosis of cutaneous melanoma (CM) was introduced in Samara, Chelyabinsk, Yekaterinburg, and Krasnodar (Russia) in 2019. Objectives: To analyze the impact of the program on early CM and non-melanoma skin cancer (NMSC) detection. Methods: According to the social educational campaign, people were informed about CM risk factors and symptoms and were invited for skin examination. The program planned to involve 3200 participants in total. Participants with suspicious lesions were invited for excisional biopsy. Results: 3143 participants, including 75.4% women, were examined for skin lesions. The average age of the participants was 43.7 years. Mostly skin phototypes II and III were registered (48.2% and 41.0%, respectively); 3 patients had CM, 15 had basal cell carcinoma, and 1 had Bowen’s disease, which were confirmed histologically. All detected melanomas had Breslow’s thickness of 1 mm. Conclusion: The participants showed high interest in early skin cancer detection programs. The incidence rate of CM and NMSCs among the program participants was higher than in general public. The early disease grade was proven for the detected CMs and NMSCs. The study has shown that it is important to continue such programs.

scholarly journals Topical Sunscreen Application Preventing Skin Cancer: Systematic Review

Cosmetics ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 42 ◽  
Author(s):  
Paola Perugini ◽  
Margherita Bonetti ◽  
Arianna Cecilia Cozzi ◽  
Giorgio Lorenzo Colombo
Keyword(s):  
Systematic Review ◽  
Skin Cancer ◽  
Topical Application ◽  
Squamous Carcinoma ◽  
Skin Lesions ◽  
Sunscreen Use ◽  
Non Melanoma Skin Cancer ◽  
Health System Cost ◽  
The Impact ◽  
Melanoma Skin

Background: Avoiding extended exposure to direct sunlight and the topical application of sunscreen when exposed are the main techniques used to protect the skin form sunburn, photoaging, and skin cancer risk (melanoma and non-melanoma skin cancer). Preventive strategies could lead to a significant reduction of the excessive health system cost for the treatment of these conditions. Sunscreen employment and efficacy stay controversial despite decades of humane use with health benefits closely related. At the present, few studies still found a connection between the use of sunscreen and not significant long-term benefits from UV induced damages. Objectives: To assess the effects of sunscreens for preventing melanoma, non-melanoma skin cancer (basal or squamous carcinoma and melanoma) and precancerous skin lesions. Method: Published literature (1993–2017) was reviewed and eligible studies that reported the impact of sunscreen use in the prevention of melanoma, non-melanoma skin cancer, or precancerous skin lesion were selected. Result: Starting from 532 sources, a total of seven articles met the inclusion criteria and they have been subjected to a systematic review. All of the included studies suggest that sunscreen use is associated with a reduction in melanoma, squamous cell carcinoma, and precancerous skin lesions; however, the difficulties in evaluating the efficiency of sunscreen were pointed out. Conclusion: The review of the experimental evidence supports the topical application of sunscreen as an effective effort in preventing skin cancer and precancerous skin lesions.

Differences on breast cancer management and surgical approach in six European breast cancer units

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 10737-10737
Author(s):  
A. Celebic ◽  
M. Halaska ◽  
O. Kosovac ◽  
D. Stojiljkovic ◽  
Z. Milovanovic ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Surgical Treatment ◽  
Surgical Approach ◽  
Frozen Section ◽  
Management Decision ◽  
Blue Dye ◽  
Cancer Management ◽  
Comparison Results ◽  
Surgical Evaluation ◽  
The Impact

10737 Background: Paper was aimed to compare differences in pre-operative management, decision on surgery and surgical approach for breast cancer in six European Breast Cancer Units in Italy, France, Czech Republic and Serbia and Montenegro, and to discuss impact of detected differences on outcome of the disease. Methods: The authors of this paper, who have been invited as young visiting/observing/training guests by four prestigious European Breast Cancer Units in Italy and France (National Cancer Institute - Milan, European Institute of Oncology - Milan, Institute Gustave Roussy - Villejuif, Institute Curie - Paris) as fellows of different European and international institutions (EUSOMA, EACR, ESSO, UICC, ESO, FECS, French Government) in the period 2003–2005, tried to detect and compare differences regarding pre-surgical evaluation, decision making and surgical approach for breast cancer as well as to discuss the impact of identified changes on outcome of the disease. The special attention has been directed to inspection of such small details as waiting list for consultation and hospitalisation, way of decision for surgical intervention (individual or oncology meeting/staff), horizontal or oblique incision for mastectomy, duration of hospital stay, sentinel node procedure (blue dye, radioactive tracer or both, one or two-days protocol, imunochistochemistry examinations during frozen section or not), preferred way of breast reconstruction, number of assistants during operation, drainage, preservation of intercostobrachial nerve during axillary surgery, suture, etc. The data were collected according to personal presence in different institutes, observation and asking the questions. Descriptive statistics were used to show the differences among the parameters under comparison. Results: This study which clearly showed a great range of differences, sometimes very significant, in parameters regarding pre-surgical evaluation and surgical treatment of breast cancer. Conclusions: Although being found, and sometimes significant, the observed differences in several parameters regarding pre-operative evaluation and surgical treatment of breast cancer in six European breast cancer units do not have influence to the outcome of the breast cancer. No significant financial relationships to disclose.

scholarly journals Complexity Theory: Artificial Intelligence System Help Safety Improvement in the Next Pandemic

2020 ◽  
Vol 5 (09) ◽  
pp. 362-368
Author(s):  
Shahad Faisal Halabi
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Complexity Theory ◽  
High Performance ◽  
New Drugs ◽  
Hospital Environment ◽  
Western World ◽  
Intelligence System ◽  
Safety Improvement ◽  
The Impact

As the coronavirus pandemic spread from Asia to the western world, drug discovery came to a near standstill. Most laboratories shut down and instruments and reagents were left untouched, except for the most essential work. The pandemic forced large and small companies, regulatory and government agencies, and academia to tap into technology, particularly artificial intelligence (AI) and machine learning (ML), for providing more than just speed and efficiency. This essay aims to dig deeply in complexity theory to help improve safety and reduce the impact of the next pandemic. It is based on implementing Artificial Intelligence (AI) to provide the safer complex theory with an example of the current situation of COVID-19. While there are no shortcuts around scientific rigor and experimentation, AI can certainly accelerate the discovery of new drugs particularly when combined with high-performance computing (HPC) and quantum computing. Evaluating new AI technologies, particularly in areas of drug discovery where there are few demonstrations of success, can be a real challenge. It is considered that safety improvement of alert systems and the risk factors, in order to organize the safety of health facilities and control the hospital environment before the potential pandemic develops. Here, we will try to apply complexity theory in our dealing with future pandemics based on the situation analysis of previous experiences.

scholarly journals Use of an artificial intelligence program in radiation therapy

2020 ◽  
Vol 58 (4) ◽  
pp. 41-43
Author(s):  
Y.I. ISHKININ ◽  
K. DATBAYEV ◽  
R. RAIMBEKOV ◽  
R. IBRAYEV ◽  
R. AKHUNOVA ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Radiation Therapy ◽  
Positive Impact ◽  
Organs At Risk ◽  
Intelligence System ◽  
Patient Registration ◽  
Patient Preparation ◽  
Workflow Efficiency ◽  
Survey Results ◽  
The Impact

Relevance: Since 01 January 2020, the provision of radiation therapy (RT) at Almaty Oncology Center was optimized using the Visual Care Path (VCP) tool of the ARIA 15.6 oncology system, which supports the implementation of sequential and parallel mandatory procedures – from patient registration to completion of treatment. The purpose was to study the impact of the implemented artificial intelligence system on RT effectiveness, safety, the share of complex RT techniques, and measure staff satisfaction and proficiency. Results: The share of intensive modulated radiation therapy sessions changed from 39.3% in 2019 to 46.6% in 2020. After the implementation of VCP, timely pre-irradiation preparation of patients (centering, delineation, dose prescription) by department doctors increased from 76% to 91%, OR = 3.2; timely measurements of plans increased from 85% to 96%, OR = 4.7; the frequency of major events (the ratio of plans with errors or unsuccessful plans to the total number of plans, delineation of organs at risk and targets, dose prescription) decreased from 12% to 3%, OR = 4.5; the frequency of minor events (late notification of the patient of the treatment commencement, timely transition to the next stage of patient preparation for treatment decreased from 32% to 10%, OR = 4.5. Staff proficiency in VCP has increased by 75%. Following the anonymous survey results, 85% of staff reported a positive impact of VCP on the workflow. Conclusion: The share of complex methods of RT has increased by 7.3%. The implementation of VCP significantly increased the workflow efficiency – by 3.9 times, reduced the number of major and minor events by 4.4 times. It allowed using a paperless communication with the executor’s identification at each stage of RT. The new technique was also quickly adopted and favorably accepted by the staff.

scholarly journals Artificial Intelligence Support for Skin Lesion Triage in Primary Care and Dermatology (Preprint)

2021 ◽  
Author(s):  
Harmony Thompson ◽  
Amanda Oakley ◽  
Michael B Jameson ◽  
Adrian Bowling
Keyword(s):  
Artificial Intelligence ◽  
Primary Care ◽  
Health Care ◽  
Skin Cancer ◽  
Sensitivity And Specificity ◽  
Health Care Access ◽  
Real Life ◽  
Primary Care Providers ◽  
Skin Lesions ◽  
Care Providers

BACKGROUND Primary care providers, dermatology specialists, and health care access are key components of primary prevention, early diagnosis, and treatment of skin cancer. Artificial intelligence (AI) offers the promise of diagnostic support for nonspecialists, but real-world clinical validation of AI in primary care is lacking. OBJECTIVE We aimed to (1) assess the reliability of an AI-based clinical triage algorithm in classifying benign and malignant skin lesions and (2) evaluate the quality of images obtained in primary care using the study camera (3Gen DermLite Cam v4 or similar). METHODS This was a single-center, prospective, double-blinded observational study with a predetermined study design. We recruited participants with suspected skin cancer in 20 primary care practices who were referred for assessment via teledermatology. A second set of photographs taken using a standardized camera was processed by the AI algorithm. We evaluated the image quality and compared two teledermatologists’ diagnoses by consensus (the “gold standard”) with AI and histology where applicable. RESULTS Our primary outcome assessment stratified 391 skin lesions by management as benign, uncertain, or malignant. Uncertain lesions were not included in the sensitivity and specificity analyses. Uncertain lesions included lesions that had either diagnostic or management uncertainties. For the remaining 242 lesions, the sensitivity was 97.26% (95% CI 93.13%-99.25%) and the specificity was 97.92% (95% CI 92.68%-99.75%). The AI algorithm was compared with the histological diagnoses for 123 lesions. The sensitivity was 100% (95% CI 95.85%-100%) and the specificity was 72.22% (95% CI 54.81%-85.80%). CONCLUSIONS The AI algorithm demonstrates encouraging results, with high sensitivity and specificity, concordant with previous AI studies. It shows potential as a triage tool in conjunction with teledermatology to augment health care and improve access to dermatology. Further real-life studies need to be conducted on a larger scale to assess the reliability, usability, and cost-effectiveness of the algorithm in primary care.

scholarly journals A regional programme to improve skin cancer management

2015 ◽  
Vol 7 (4) ◽  
pp. 339 ◽  
Author(s):  
Graham McGeoch ◽  
Mark Sycamore ◽  
Brett Shand ◽  
Jeremy Simcock
Keyword(s):  
General Practice ◽  
Skin Cancer ◽  
Cancer Treatment ◽  
Secondary Care ◽  
Waiting Times ◽  
Skin Neoplasms ◽  
Skin Lesions ◽  
Care Quality ◽  
Cancer Management ◽  
Care Services

BACKGROUND AND CONTEXT: In 2008, public specialist and general practice services in Canterbury were unable to manage demand for skin cancer treatment. Local clinicians decided the solution was to develop a see-and-treat skin excision clinic staffed by plastic surgeons and general practitioners (GPs), and the introduction of subsidised excisions in general practice. This paper describes the collaboration between clinicians, managers and funders and the results and quality management measures of these initiatives. ASSESSMENT OF PROBLEM: There is an increasing incidence of skin cancer. GPs in Canterbury were unable to meet increasing demand for skin cancer treatment because some lacked confidence and competence in skin cancer management. There was no public funding for primary care management of skin cancer, driving patients to fully funded secondary care services. Secondary care services were at capacity, with no coordinated programme across primary and secondary care. RESULTS: The programme has resulted in a greater number of skin cancers being treated by the public health system, a reduction in waiting times for treatment, and fewer minor skin lesions being referred to secondary care. Quality measures have been achieved and are improving steadily. Development of the programme has improved working relationships between primary and secondary care clinicians. STRATEGIES FOR IMPROVEMENT: The strategy was to facilitate the working relationship between primary and secondary care and increase the capacity for skin lesion excisions in both sectors. LESSONS: Skin cancer management can be improved by a coordinated approach between primary and secondary care. KEYWORDS: Continuing medical education; general practice; minor surgical procedures; referral and consultation; skin neoplasms

scholarly journals Artificial Intelligence Support for Skin Lesion Triage in Primary Care and Dermatology

Iproceedings ◽  
10.2196/35395 ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. e35395
Author(s):  
Harmony Thompson ◽  
Amanda Oakley ◽  
Michael B Jameson ◽  
Adrian Bowling
Keyword(s):  
Artificial Intelligence ◽  
Primary Care ◽  
Health Care ◽  
Skin Cancer ◽  
Sensitivity And Specificity ◽  
Conflicts Of Interest ◽  
Real Life ◽  
Primary Care Providers ◽  
Skin Lesions ◽  
Care Providers

Background Primary care providers, dermatology specialists, and health care access are key components of primary prevention, early diagnosis, and treatment of skin cancer. Artificial intelligence (AI) offers the promise of diagnostic support for nonspecialists, but real-world clinical validation of AI in primary care is lacking. Objective We aimed to (1) assess the reliability of an AI-based clinical triage algorithm in classifying benign and malignant skin lesions and (2) evaluate the quality of images obtained in primary care using the study camera (3Gen DermLite Cam v4 or similar). Methods This was a single-center, prospective, double-blinded observational study with a predetermined study design. We recruited participants with suspected skin cancer in 20 primary care practices who were referred for assessment via teledermatology. A second set of photographs taken using a standardized camera was processed by the AI algorithm. We evaluated the image quality and compared two teledermatologists’ diagnoses by consensus (the “gold standard”) with AI and histology where applicable. Results Our primary outcome assessment stratified 391 skin lesions by management as benign, uncertain, or malignant. Uncertain lesions were not included in the sensitivity and specificity analyses. Uncertain lesions included lesions that had either diagnostic or management uncertainties. For the remaining 242 lesions, the sensitivity was 97.26% (95% CI 93.13%-99.25%) and the specificity was 97.92% (95% CI 92.68%-99.75%). The AI algorithm was compared with the histological diagnoses for 123 lesions. The sensitivity was 100% (95% CI 95.85%-100%) and the specificity was 72.22% (95% CI 54.81%-85.80%). Conclusions The AI algorithm demonstrates encouraging results, with high sensitivity and specificity, concordant with previous AI studies. It shows potential as a triage tool in conjunction with teledermatology to augment health care and improve access to dermatology. Further real-life studies need to be conducted on a larger scale to assess the reliability, usability, and cost-effectiveness of the algorithm in primary care. Acknowledgments MoleMap NZ, who developed the AI algorithm, provided some funding for this study. HT's salary was partially sponsored by MoleMap NZ, who developed the AI algorithm. AB is a shareholder and consultant to Molemap Ltd provider of the AI algorithm. Conflicts of Interest None declared.

scholarly journals Prospects of the Development of Artificial Intelligence in the World Arena

2020 ◽  
Vol 6 (2) ◽  
pp. 58-64
Author(s):  
N.S. Deshevykh ◽  
◽  
V.V. Yudaev ◽  
Keyword(s):  
Artificial Intelligence ◽  
Developed Countries ◽  
Intelligence System ◽  
Technological Potential ◽  
The World ◽  
Artificial Intelligence Technology ◽  
Technological Developments ◽  
The Third World ◽  
Political Governance ◽  
The Impact

today, the development of the artificial intelligence system determines a number of processes of an international nature. Earlier technological developments formed the internal technological potential of the country and did not go beyond the framework of the national state, but today artificial intelligence forms a spectrum of trends on the world stage. This article analyzes the impact of artificial intelligence on international relations, examined the possible risks and threats that countries may face as a result of the generation of artificial intelligence technology. The objective of the study is to investigate the possible prospects for the development of artificial intelligence systems, as well as the impact of the application of artificial intelligence technology on the world stage. It was found that the upcoming era of robotics entails, along with military and economic risks, radical changes in the field of global political governance. First of all, this is due to the fact that the possession of artificial intelligence technologies will finally bridge the gap between developed countries and the third world, and also make it insurmountable. In conclusion, the author proposed measures to minimize threats to the use of artificial intelligence technology on the world stage.

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