Dan Mullarkey
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View article: P007 Comparative real-world performance of an artificial intelligence as a medical device and consultant teledermatologists in diagnosing benign skin lesion subtypes
P007 Comparative real-world performance of an artificial intelligence as a medical device and consultant teledermatologists in diagnosing benign skin lesion subtypes Open
Providing a consistent diagnosis is helpful when reassuring and discharging patients with benign skin lesions. A UK Conformity Assessed (UKCA) class IIa artificial intelligence as a medical device (AIaMD) classifies lesions with specific b…
View article: AI12 Prospective, multicentre, real-world sensitivities of an artificial intelligence as a medical device assessment and teledermatologist assessment in appropriately managing melanoma, squamous cell carcinoma and rare skin cancers referred on the urgent suspected cancer pathway
AI12 Prospective, multicentre, real-world sensitivities of an artificial intelligence as a medical device assessment and teledermatologist assessment in appropriately managing melanoma, squamous cell carcinoma and rare skin cancers referred on the urgent suspected cancer pathway Open
Melanoma, squamous cell carcinoma (SCC) and rare cancers are high-risk lesions that should be managed via the National Health Service Urgent Suspected Cancer (USC) pathway. This study reports on the real-world sensitivities of assessments …
View article: AI15 The use of artificial intelligence as a medical device and teledermatology in the assessment of Merkel cell carcinoma: a National Health Service case series
AI15 The use of artificial intelligence as a medical device and teledermatology in the assessment of Merkel cell carcinoma: a National Health Service case series Open
This case series presents instances of detection of Merkel cell carcinoma (MCC) by both teledermatologists and a UK Conformity Assessed class IIa artificial intelligence as a medical device (AIaMD) in National Health Service (NHS) skin can…
View article: P042 Developing a clinical audit methodology for monitoring dermatologist performance in artificial intelligence-enabled teledermatology pathways
P042 Developing a clinical audit methodology for monitoring dermatologist performance in artificial intelligence-enabled teledermatology pathways Open
Teledermatology can help support the timely diagnosis of skin cancer. NHS England recently published a roadmap to accelerate the roll-out of teledermatology services nationally, including an updated series of audit and quality control stan…
View article: Response: Commentary: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Response: Commentary: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance Open
This is the final version. Available on open access from Frontiers Media via the DOI in this record
View article: Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service
Accuracy of an artificial intelligence as a medical device as part of a UK-based skin cancer teledermatology service Open
Introduction An artificial intelligence as a medical device (AIaMD), built on convolutional neural networks, has demonstrated high sensitivity for melanoma. To be of clinical value, it needs to safely reduce referral rates. The primary obj…
View article: Artificial Intelligence in Cutaneous Lesions: Where do we Stand and What is Next?
Artificial Intelligence in Cutaneous Lesions: Where do we Stand and What is Next? Open
it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed.The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge.Front…
View article: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance Open
Introduction Deep Ensemble for Recognition of Malignancy (DERM) is an artificial intelligence as a medical device (AIaMD) tool for skin lesion assessment. Methods We report prospective real-world performance from its deployment within skin…
View article: Effectiveness of an image analyzing AI-based Digital Health Technology to identify Non-Melanoma Skin Cancer and other skin lesions: results of the DERM-003 study
Effectiveness of an image analyzing AI-based Digital Health Technology to identify Non-Melanoma Skin Cancer and other skin lesions: results of the DERM-003 study Open
Introduction Identification of skin cancer by an Artificial Intelligence (AI)-based Digital Health Technology could help improve the triage and management of suspicious skin lesions. Methods The DERM-003 study (NCT04116983) was a prospecti…
View article: BT09 Clinical performance of an artificial intelligence-based medical device deployed within an urgent suspected skin cancer pathway
BT09 Clinical performance of an artificial intelligence-based medical device deployed within an urgent suspected skin cancer pathway Open
A secondary care trust received over 2800 urgent suspected skin cancer referrals (USCRs) in 2021, 50% more than in 2016 (www.england.nhs.uk/statistics/statistical-work-areas/cancer-waiting-times), < 1 in 10 of which resulted in diagnosi…
View article: BT06 Using artificial intelligence to triage skin cancer referrals: outcomes from a pilot study
BT06 Using artificial intelligence to triage skin cancer referrals: outcomes from a pilot study Open
Artificial intelligence (AI) is a rapidly emerging field in dermatology, aimed at delivering efficient and effective patient care. To date, there is a lack of substantial evidence for the use of this technology in a clinical setting. Howev…
View article: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance Open
Deep Ensemble for Recognition of Malignancy (DERM) is an artificial intelligence as a medical device (AIaMD) tool for skin lesion assessment. We report prospective real-world performance from its deployment within skin cancer pathways at t…
View article: Attitudes towards Trusting Artificial Intelligence Insights and Factors to Prevent the Passive Adherence of GPs: A Pilot Study
Attitudes towards Trusting Artificial Intelligence Insights and Factors to Prevent the Passive Adherence of GPs: A Pilot Study Open
Artificial Intelligence (AI) systems could improve system efficiency by supporting clinicians in making appropriate referrals. However, they are imperfect by nature and misdiagnoses, if not correctly identified, can have consequences for p…
View article: A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis
A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis Open
AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a mean…
View article: Integrated care through training – joint general practitioner/geriatric trainee clinics
Integrated care through training – joint general practitioner/geriatric trainee clinics Open
ConclusionsThere was qualitative evidence of learning from the GP and geriatric trainees, with good formal feedback from patients.This pilot project provided an exciting template to improve training of both GPs and geriatricians, improve t…
View article: A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis
A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis Open
Online symptom checkers have significant potential to improve patient care, however their reliability and accuracy remain variable. We hypothesised that an artificial intelligence (AI) powered triage and diagnostic system would compare fav…