AIMC Topic: Skin Neoplasms
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Ethical implications of artificial intelligence in skin cancer diagnostics: use-case analyses.
The British journal of dermatology
Feb 18, 2025
BACKGROUND: Skin cancer is the most common cancer worldwide. Early diagnosis is crucial to improving patient survival and morbidity. Artificial intelligence (AI)-assisted smartphone applications (apps) for skin cancer potentially offer accessible, ea...
Artificial intelligence in dermatopathology: a systematic review.
Clinical and experimental dermatology
Jan 27, 2025
Medical research, driven by advancing technologies like artificial intelligence (AI), is transforming healthcare. Dermatology, known for its visual nature, benefits from AI, especially in dermatopathology with digitized slides. This review explores A...
Advances in computer vision and deep learning-facilitated early detection of melanoma.
Briefings in functional genomics
Jan 15, 2025
Melanoma is characterized by its rapid progression and high mortality rates, making early and accurate detection essential for improving patient outcomes. This paper presents a comprehensive review of significant advancements in early melanoma detect...
[Research advances in the pathological diagnosis of melanocytic tumors with artificial intelligence].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Jan 8, 2025
Hybrid of Deep Feature Extraction and Machine Learning Ensembles for Imbalanced Skin Cancer Datasets.
Experimental dermatology
Dec 1, 2024
Skin cancer remains one of the most common and deadly forms of cancer, necessitating accurate and early diagnosis to improve patient outcomes. In order to improve classification performance on unbalanced datasets, this study proposes a distinctive ap...
Melanoma imaging and diagnosis: What does the future hold?
Australian journal of general practice
Sep 1, 2024
BACKGROUND: In Australia, artificial intelligence (AI) is increasingly being used in the field of melanoma diagnosis. Early diagnosis is arguably the most important prognostic factor for melanoma survival. The use of digital monitoring of naevi, espe...
A novel Skin lesion prediction and classification technique: ViT-GradCAM.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
Sep 1, 2024
BACKGROUND: Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinica...
Patient-led skin cancer teledermatology without dermoscopy during the COVID-19 pandemic: important lessons for the development of future patient-facing teledermatology and artificial intelligence-assisted -self-diagnosis.
Clinical and experimental dermatology
Aug 22, 2024
MySkinSelfie is a mobile phone application for skin self-monitoring, enabling secure sharing of patient-captured images with healthcare providers. This retrospective study assessed MySkinSelfie's role in remote skin cancer assessment at two centres f...
Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model training. Synthetic data plays a pivotal role in mitigating challenges ...
Lesion Segmentation in Skin Cancer Images using Fusion Model via Deep Learning Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Skin cancer, one of the most prevalent and life-threatening cancers globally, has become a focus of deep learning applications due to its significant impact on diagnostic accuracy. This research specifically addresses lesion segmentation in skin canc...
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