☆ 4.7 Article Data Paper

A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models

SCIENTIFIC DATA (2023)

Related references

Note: Only part of the references are listed.

Review Oncology

Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review

Andres Mosquera-Zamudio et al.

Summary: Deep learning has shown promising outcomes in surgical pathology, particularly in dermatopathology, for melanocytic tumors in whole slide images. This study analyzes previously published studies on deep learning techniques for automatic image analysis of melanocytic tumors. The analysis reveals research trends in diagnostic prediction, prognosis, and regions of interest, and emphasizes the considerations for implementing these models in real scenarios. The rise of artificial intelligence as a support tool in clinical pathology workflows is also highlighted.

CANCERS (2023)

Add to Collection

Review Chemistry, Analytical

New Trends in Melanoma Detection Using Neural Networks: A Systematic Review

Dan Popescu et al.

Summary: This paper presents a systematic review of recent advances in using artificial intelligence, especially neural network-based systems, for the early detection and diagnosis of melanoma. The study finds that such systems have shown high accuracy and efficiency in detecting and diagnosing melanoma at the early stages.

SENSORS (2022)

Add to Collection

Review Dermatology

BAPoma presenting as an incidental scalp papule: case report, literature review, and screening recommendations for BAP1 tumor predisposition syndrome

Marcus Zaayman et al.

Summary: BAP1-associated protein 1 (BAP1) tumor predisposition syndrome (BAP1-TPDS) is associated with an increased risk of aggressive cancers, with BAP1-inactivated melanocytic tumors (BIMTs) often serving as a predictive marker for identifying patients at higher risk of associated cancers. Genetic evaluation is recommended for patients with multiple BIMTs or significant family history of BAP1-TPDS related cancers, with cancer surveillance for early diagnosis and intervention improving outcomes.

JOURNAL OF DERMATOLOGICAL TREATMENT (2022)

Add to Collection

Review Oncology

The Spectrum of Spitz Melanocytic Lesions: From Morphologic Diagnosis to Molecular Classification

Tiffany W. Cheng et al.

Summary: Spitz tumors are a distinct subtype of melanocytic lesions with characteristic histopathologic features. They are more common in pediatric and younger population. Specific patterns on dermatoscopic examination can help in clinical suspicion. These tumors can be classified into benign, intermediate, and malignant subtypes. Recent research has revealed the molecular underpinning of Spitz tumors.

FRONTIERS IN ONCOLOGY (2022)

Add to Collection

Proceedings Paper Computer Science, Software Engineering

MULTI-RESOLUTION FRAMEWORK FOR SPITZOID NEOPLASM CLASSIFICATION USING HISTOLOGICAL DATA

Rocio Del Amor et al.

Summary: A multi-resolution framework has been proposed for the automatic assessment of morphological features at different resolution levels in Spitzoid melanocytic tumors, outperforming single-resolution frameworks in SMT classification according to experiments.

2022 IEEE 14TH IMAGE, VIDEO, AND MULTIDIMENSIONAL SIGNAL PROCESSING WORKSHOP (IVMSP) (2022)

Add to Collection

Review Dermatology

Artificial Intelligence in Dermatopathology: New Insights and Perspectives

Gerardo Cazzato et al.

Summary: In recent years, there has been a growing interest in artificial intelligence and machine learning in the field of medicine. The dermatopathological field is also beginning to explore the development and training of algorithms to aid pathologists in the differential diagnosis of complex melanocytic lesions, although still in its early stages. This new challenge presents promising future prospects in the modern era.

DERMATOPATHOLOGY (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

An attention-based weakly supervised framework for spitzoid melanocytic lesion diagnosis in whole slide images

Rocio del Amor et al.

Summary: A novel end-to-end weakly supervised deep learning model based on inductive transfer learning with an improved convolutional neural network (CNN) was proposed for the analysis of spitzoid lesions in skin cancer. The model demonstrated high accuracy in distinguishing between benign and malignant forms of melanoma, outperforming traditional diagnostic methods. Heat map findings correlated well with clinical decisions and enhanced the identification of patterns of interest in some cases.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2021)

Add to Collection

Review Oncology

Original Research Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts

Sarah Haggenmueller et al.

Summary: The study systematically analyzed the research status of reader studies involving melanoma and found that CNN-based classifiers demonstrated superior or at least equivalent performance compared with clinicians. However, it was noted that most studies were conducted in highly artificial settings, with test sets not representing the full range of patient populations and melanoma subtypes encountered in clinical practice.

EUROPEAN JOURNAL OF CANCER (2021)

Add to Collection

Article Dermatology

Integrating Next-Generation Sequencing with Morphology Improves Prognostic and Biologic Classification of Spitz Neoplasms

Victor L. Quan et al.

JOURNAL OF INVESTIGATIVE DERMATOLOGY (2020)

Add to Collection

Review Computer Science, Artificial Intelligence

Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential

Maximilian E. Tschuchnig et al.

PATTERNS (2020)

Add to Collection

Review Dermatology

The role of gene fusions in melanocytic neoplasms

Victor L. Quan et al.

JOURNAL OF CUTANEOUS PATHOLOGY (2019)

Add to Collection

Review Dermatology

BRCA1-associated protein (BAP1)-inactivated melanocytic tumors

Arianna J. Zhang et al.

JOURNAL OF CUTANEOUS PATHOLOGY (2019)

Add to Collection

Article Pathology

The complex management of atypical Spitz tumours

Daniela Massi et al.

PATHOLOGY (2016)

Add to Collection

Article Pathology

Genomic aberrations in spitzoid melanocytic tumours and their implications for diagnosis, prognosis and therapy

Thomas Wiesner et al.

PATHOLOGY (2016)

Add to Collection

Article Medical Laboratory Technology

Atypical Spitz Tumors A Diagnostic Challenge

Kelly L. Harms et al.

ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE (2015)

Add to Collection

Article Medicine, Research & Experimental

BAP1 cancer syndrome: malignant mesothelioma, uveal and cutaneous melanoma, and MBAITs

Michele Carbone et al.

JOURNAL OF TRANSLATIONAL MEDICINE (2012)

Add to Collection

© Peeref 2019-2024. All rights reserved.