A5058597483- AI in cancer detection
- Cutaneous Melanoma Detection and Management
- Digital Imaging for Blood Diseases
- Radiomics and Machine Learning in Medical Imaging
- Cell Image Analysis Techniques
- Privacy-Preserving Technologies in Data
- melanin and skin pigmentation
- Artificial Intelligence in Healthcare and Education
- Nonmelanoma Skin Cancer Studies
- Brain Tumor Detection and Classification
- Air Traffic Management and Optimization
- Melanoma and MAPK Pathways
- Cancer Genomics and Diagnostics
- Aerospace and Aviation Technology
- Machine Learning in Healthcare
- Inflammatory Bowel Disease
- Laser Material Processing Techniques
- Advanced Measurement and Metrology Techniques
- Human-Automation Interaction and Safety
- Mycobacterium research and diagnosis
- Colorectal Cancer Screening and Detection
- COVID-19 diagnosis using AI
- Anomaly Detection Techniques and Applications
- Advanced machining processes and optimization
Universitat Politècnica de València
2021-2025
Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) affecting the colon and rectum characterized by a remitting-relapsing course. To detect mucosal inflammation associated with UC, histology considered most stringent criteria. In turn, histologic remission (HR) correlates improved clinical outcomes has been recently recognized as desirable treatment target. The leading biomarker for assessing presence or absence of neutrophils. Therefore, finding this cell in specific structures...
Spitzoid tumors (ST) are a group of melanocytic high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the uncertainty remains until now, especially in intermediate category known as tumor unknown malignant potential (STUMP) or atypical tumor. Studies developing deep learning (DL) models to diagnose using whole slide imaging (WSI) scarce, and few used ST for analysis, excluding STUMP. To address this gap, we introduce SOPHIE: dataset with WSIs, including labels...
Deep learning-based algorithms have led to tremendous progress over the last years, but they face a bottleneck as their optimal development highly relies on access large datasets. To mitigate this limitation, cross-silo federated learning has emerged way train collaborative models among multiple institutions without having share raw data used for model training. However, although artificial intelligence experts expertise develop state-of-the-art and actively code through notebook...
The histopathological classification of melanocytic tumours with spitzoid features remains a challenging task. We confront the complexities involved in histological these by proposing machine learning (ML) algorithms that objectively categorise most relevant order importance. data set comprises 122 (39 benign, 44 atypical and 39 malignant) from four different countries. BRAF NRAS mutation status was evaluated 51. Analysis variance score performed to rank 22 clinicopathological variables....
Spitzoid melanocytic tumors (SMTs) are a group of neoplasms that represent formidable diagnostic challenge for experts. In daily practice, dermatopathologists examine tissue biopsies manually, which is very time-consuming. To perform an effective diagnosis, pathologists visualize the histological features these at different resolution levels, as lesion contours (visualized low level) and morphology cells (at high decisive. Aiming to mimic practice dermatopathologist, in this paper, we...
The digitization of biopsies into high-resolution whole-slide images has opened the way to artificial intelligence methods in pathology. While histopathological analysis remains gold standard for cancer diagnosis, deep learning holds great potential reducing pathologist workload and enhancing diagnosis. This can be particularly crucial tumors with ambiguous morphological features like spitzoid melanocytic lesions, where these could greatly improve their clinical interpretation. However,...
Melanoma is an aggressive neoplasm responsible for the majority of deaths from skin cancer. Specifically, spitzoid melanocytic tumors are one most challenging lesions due to their ambiguous morphological features. The gold standard its diagnosis and prognosis analysis biopsies. In this process, dermatopathologists visualize histology slides under a microscope, in high time-consuming subjective task. last years, computer-aided (CAD) systems have emerged as promising tool that could support...
The advent of artificial intelligence-based tools applied to digital pathology brings the promise reduced workload for pathologists and enhanced patient care, not mention medical research progress. Yet, despite its great potential, field is hindered by paucity annotated histological data, a limitation developing robust deep learning models. To reduce number expert annotations needed training, we introduce novel framework combining self-training weakly-supervised that uses both unannotated...
Background and Objective: Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) affecting the colon rectum characterized by a remitting-relapsing course. To detect mucosal inflammation associated with UC, histology considered most stringent criteria. In turn, histologic remission (HR) correlates improved clinical outcomes has been recently recognized as desirable treatment target. The leading biomarker for assessing presence or absence of neutrophils. Therefore, finding this cell in...