Burns Open, Journal Year: 2024, Volume and Issue: 9, P. 100389 - 100389
Published: Dec. 11, 2024
Language: Английский
BMC Medical Informatics and Decision Making, Journal Year: 2025, Volume and Issue: 25(1)
Published: Jan. 8, 2025
Language: Английский
Citations
1
Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104682 - 104682
Published: March 1, 2025
Brain tumors refer to the abnormal growths that occur within brain's tissue, comprising both primary neoplasms and metastatic lesions. Timely detection, precise staging, suitable treatment, standardized management are of significant clinical importance for extending survival rates brain tumor patients. Artificial intelligence (AI), a discipline computer science, is leveraging its robust capacity information identification combination revolutionize traditional paradigms oncology care, offering substantial potential precision medicine. This article provides an overview current applications AI in tumors, encompassing technologies, their working mechanisms workflow, contributions diagnosis as well role scientific research, particularly drug innovation revealing microenvironment. Finally, paper addresses existing challenges, solutions, future application prospects. review aims enhance our understanding provide valuable insights forthcoming inquiries.
Language: Английский
Citations
1
Journal of Wound Care, Journal Year: 2025, Volume and Issue: 34(Sup4b), P. S1 - S25
Published: March 20, 2025
Language: Английский
Citations
1
Journal of Medicine Surgery and Public Health, Journal Year: 2025, Volume and Issue: unknown, P. 100189 - 100189
Published: March 1, 2025
Language: Английский
Citations
0
Life, Journal Year: 2024, Volume and Issue: 14(12), P. 1602 - 1602
Published: Dec. 4, 2024
Skin cancer is one of the most prevalent cancers worldwide, with increasing incidence. typically classified as melanoma or non-melanoma skin cancer. Although less common than basal squamous cell carcinomas, it deadliest form cancer, nearly 8300 Americans expected to die from each year. Biopsies are currently gold standard in diagnosing melanoma; however, they can be invasive, expensive, and inaccessible lower-income individuals. Currently, suspicious lesions triaged image-based technologies, such dermoscopy confocal microscopy. While these techniques useful, there wide inter-user variability minimal training for dermatology residents on how properly use devices. The artificial intelligence (AI)-based technologies has emerged recent years assist diagnosis that may more accessible all patients accurate current methods screening. This review explores status application AI-based algorithms detection melanoma, underscoring its potential aid dermatologists clinical practice. We specifically focus AI imaging, dermoscopic evaluation, distinguish cancers, vivo imaging
Language: Английский
Citations
2
Clinical and Experimental Dermatology, Journal Year: 2024, Volume and Issue: 49(7), P. 671 - 674
Published: May 9, 2024
Language: Английский
Citations
1
JEADV Clinical Practice, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 10, 2024
Since artificial intelligence (AI) has widely shown applications for skin cancer diagnosis, creating comprehensive image datasets is key.1-4 Availability of databases are increasing, with a low representation higher phototypes, certain ethnic groups, and limited metadata.5 Excluding specific populations perpetuates healthcare disparities in the AI era.6 Due to lack diverse datasets, external use validation algorithms not currently possible our population. We started project create Chilean database: The 'Trawa' database ('skin' Mapuzungun, native language). This study aims describe current dataset characteristics along limitations during its creation. was retrospective approved by local Institutional Review Board (IRB). images were collected from January 2019 December 2020, four dermatologists working Tertiary Care Academic Hospital. Clinical dermoscopy obtained variable smartphones. All included lesions biopsy-proven. Metadata (i.e., age, sex, anatomical location, histopathological details, relevant past medical story, phototype) electronic records. Cases coded folder. data stored Health Insurance Portability Accountability Act (HIPAA)-compliant web hosting. During period, we 860 individual cases consisting 4435 clinical (Figure 1), organized seven categories: actinic keratosis, basal cell carcinoma, cutaneous squamous melanoma, naevus, seborrhoeic keratosis others (angiomas, warts, etc.) (Table regarding metadata 52.6% women; average age 54 years; 32.8% had photodamage 70.2% phototype III. Most located on head neck (50.6%); 26.8% diagnosis malignant. A various conditions high-quality images. have biopsy-proven cases, including categories 1). Accurate annotations data. Every case histopathologic confirmation. Considering that adding gives better accuracy AI,8 metadata. availability scarce. Continual updates, as technology quickly updating, new imaging modalities appear. For example, now incorporating ultraviolet-dermoscopy Privacy security measures: should be according HIPAA without identifiable patient features. cardinal point when using contrast dermoscopy. Respect ethical considerations. Local IRB approval mandatory followed. Finally, also suggest multidisciplinary teams composed computer science professionals. Creating improving will augment performance algorithms,9 us, this necessary step performing collaborative work other countries region (e.g., Latin America).3 Potential include algorithm training fine-tuned well comparing different databases. main relatively small size. Organising requires large team multiple resources. Also, only histopathology confirmation, biasing towards more 'suspicious' lesions. Using noninvasive technologies such reflectance confocal microscopy could an alternative nonbiopsied benign lesions.10 Acquisition, analysis, interpretation data: Leonel Hidalgo, María Paz Salinas, Javiera Sepúlveda, Karina Carrasco, Pamela Romero, Alma Pedro, Soledad Vidaurre, Domingo Mery Cristian Navarrete-Dechent. Drafting revising article: Final version published: funded part ANID—Millennium Science Initiative Programme ICN2021_004. authors declare no conflict interest. Reviewed Scientific Ethical Committee Sciences Pontificia Universidad Católica de Chile; #211213001. support findings available corresponding author upon reasonable request.
Language: Английский
Citations
1
Burns Open, Journal Year: 2024, Volume and Issue: 9, P. 100389 - 100389
Published: Dec. 11, 2024
Language: Английский
Citations
0