Publications by authors named "Andres Mosquera-Zamudio"

Large nested melanomas (LNMs) are a rare subtype of naevoid melanoma consisting of large junctional melanocytic nests that are more common in older individuals and/or associated with sun damage. However, the presence of large melanocytic nests alone does not lead to a diagnosis of malignancy, ​as they can also be found in melanocytic naevi. LNMs are challenging because they lack most classic histological features of malignancy and require thorough clinicopathological evaluation.

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Background: Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures result in the introduction of artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs).

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In Colombia, cancer is recognized as a high-cost pathology by the national government and the Colombian High-Cost Disease Fund. As of 2020, the situation is most critical for adult cancer patients, particularly those under public healthcare and residing in remote regions of the country. The highest lag time for a diagnosis was observed for cervical cancer (79.

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Article Synopsis
  • The classification of melanocytic tumours with spitzoid features is complex, and a study proposes machine learning algorithms to objectively categorize these tumours based on important histological features.
  • The analysis involved 122 tumours (benign, atypical, and malignant) and evaluated mutation status for some, using various algorithms that showed high accuracy in distinguishing between different types of tumours.
  • The results suggest that machine learning can enhance the classification process in clinical practice, improving diagnosis and reducing inconsistencies among different observers.
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Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the diagnostic uncertainty remains until now, especially in the intermediate category known as Spitz tumor of unknown malignant potential (STUMP) or atypical Spitz tumor. Studies developing deep learning (DL) models to diagnose melanocytic tumors using whole slide imaging (WSI) are scarce, and few used ST for analysis, excluding STUMP.

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The rise of Artificial Intelligence (AI) has shown promising performance as a support tool in clinical pathology workflows. In addition to the well-known interobserver variability between dermatopathologists, melanomas present a significant challenge in their histological interpretation. This study aims to analyze all previously published studies on whole-slide images of melanocytic tumors that rely on deep learning techniques for automatic image analysis.

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Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin cancer. Specifically, spitzoid melanocytic tumors are one of the most challenging melanocytic lesions due to their ambiguous morphological features. The gold standard for its diagnosis and prognosis is the analysis of skin biopsies.

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Gastrointestinal bleeding in HIV patients secondary to coinfection by HHV8 and development of Kaposi's sarcoma (KS) is a rare complication even if no skin lesions are detected on physical examination. This article indicates which patients might develop this type of clinical sign and also tries to recall that absence of skin lesions never rules out the presence of KS, especially if gastrointestinal involvement is documented. Gastrointestinal bleeding in terms of hematemesis has rarely been reported in the literature.

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Introduction: There is an emerging need for telecytology in Colombia as the demand for cytopathology has increased. However, due to economic and technological constraints telecytology services are limited. Our aim was to evaluate the diagnostic feasibility of using whole slide imaging with and without Z-stacking for telecytology in Colombia, South America.

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