AIMC Topic: Skin Neoplasms

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Formative Usability Testing of Artificial Intelligence in Pathology: The Challenge of Assessing Acceptability.

Studies in health technology and informatics
Digital Pathology has provided a platform to use Artificial Intelligence (AI) to assist pathologists with diagnosis and reporting. An AI tool is being developed that analyzes digital Hematoxylin and Eosin (stained tissue) images associated with a ski...

A fusocelular skin dataset with whole slide images for deep learning models.

Scientific data
Cutaneous spindle cell (CSC) lesions encompass a spectrum from benign to malignant neoplasms, often posing significant diagnostic challenges. Computer-aided diagnosis systems offer a promising solution to make pathologists' decisions objective and fa...

A customizable P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing.

Journal of materials chemistry. B
Skin hemangioma is a tumor originating from skin blood vessels, which often occurs in infants and children. Brachytherapy with the P-based radionuclide applicator is an effective non-invasive therapeutic method. However, the inordinance of lesions is...

Mobile health apps for skin cancer triage in the general population: a qualitative study on healthcare providers' perspectives.

BMC cancer
BACKGROUND: Mobile health (mHealth) applications (apps) integrated with artificial intelligence for skin cancer triage are increasingly available to the general public. Nevertheless, their actual uptake is limited. Although endorsement by healthcare ...

[ARTIFICIAL INTELLIGENCE-ASSISTED LITERATURE REVIEW: A CASE STUDY IN FUMARATE HYDRATASE-DEFICIENT RENAL CELL CARCINOMA].

Harefuah
Fumarate hydratase-deficient renal cell carcinoma (FHdRCC) is a rare and aggressive form of kidney cancer that presents significant therapeutic challenges. Due to its rarity, treatment decisions often rely on comprehensive literature reviews to ident...

Deep Learning-Based Classification of Early-Stage Mycosis Fungoides and Benign Inflammatory Dermatoses on H&E-Stained Whole-Slide Images: A Retrospective, Proof-of-Concept Study.

The Journal of investigative dermatology
The diagnosis of early-stage mycosis fungoides (MF) is challenging owing to shared clinical and histopathological features with benign inflammatory dermatoses. Recent evidence has shown that deep learning (DL) can assist pathologists in cancer classi...

Ethical implications of artificial intelligence in skin cancer diagnostics: use-case analyses.

The British journal of dermatology
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
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
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...