Policy Challenges in Ultra-Rare Cancers: Ethical, Social, and Legal Implications of Melanoma Prevention and Diagnosis in Children, Adolescents, and Young Adults

Healthcare, Journal Year: 2025, Volume and Issue: 13(3), P. 321 - 321

Published: Feb. 4, 2025

Background: The ultra-rare nature of melanoma in children, adolescents, and young adults poses significant challenges to the development implementation effective prevention diagnostic strategies. This article delves into ELSIs surrounding these strategies, placing particular emphasis on transformative potential AI-driven tools applications. Methods: Using an exploratory sequential mixed methods approach, this study integrated a PICO-guided literature review qualitative insights from two focus groups. included 26 peer-reviewed articles published English January 2019 2024, addressing melanoma, rare diseases, AI dermatology. Focus groups March 2024 session Berlin with 15 stakeholders (patients, caregivers, advocates, healthcare professionals) November online 5 interdisciplinary experts. Results: Six key priorities for policies emerged: cultural factors, such as glorification tanned skin; enhancing professional training accurate diagnosis; balancing risks overdiagnosis underdiagnosis; promoting patient autonomy through transparent communication; reducing inequalities ensure equitable access care; making ethical legal use healthcare. Conclusion: These provide comprehensive framework advancing diagnosis adults, leveraging technologies while prioritizing patient-centered delivery.

Language: Английский

Unveiling Lung Diseases in CT Scan Images With a Hybrid Bio‐Inspired Mutated Spider‐Monkey and Crow Search Algorithm

Expert Systems, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

ABSTRACT Bio‐inspired computer‐aided diagnosis (CAD) has garnered significant attention in recent years due to the inherent advantages of bio‐inspired evolutionary algorithms (EAs) handling small datasets with elevated precision and reduced computational complexity. Traditional CAD models face limitations as they can only be developed post‐outbreak, relying on that become available during such events COVID‐19 pandemic. The scarcity data for emerging diseases poses a substantial challenge achieving conventional deep‐learning algorithms. Furthermore, even when are available, employing deep learning class‐based classification is arduous, necessitating model retraining, this paper, we propose novel hybrid algorithm leverages strengths crow search (CSA) spider monkey optimization (SMO) create an optimised (OSM‐CS) algorithm. We tool maps each input CT image high‐dimensional vector by extracting four categories features: high contrast, polynomial decomposition, textural, pixel statistics. proposed OSM‐CS employed feature selection method. Our experimental results demonstrate effectiveness algorithm, impressive accuracy 98.2% coupled AdaBoost classifier multi‐class 99.93% binary classification. This performance surpasses state‐of‐the‐art (SOTA) recently published algorithms, underscoring potential powerful realm CAD.

Language: Английский

Accuracy of Rhythm Diagnostic Systems’ MultiSense® in Detection of Arterial Oxygen Saturation and Respiratory Rate During Hypoxia in Humans: Effects of Skin Color and Device Localization

Sensors, Journal Year: 2024, Volume and Issue: 25(1), P. 127 - 127

Published: Dec. 28, 2024

The continuous monitoring of oxygen saturation (SpO2) and respiratory rates (RRs) are major clinical issues in many cardio-respiratory diseases have been tremendous importance during the COVID-19 pandemic. early detection hypoxemia was crucial since it precedes significant complications, SpO2 follow-up allowed hospital discharge patients needing therapy. Nevertheless, fingertip devices showed some practical limitations. In this study, we investigated reliability new Multisense® pulse oximetry system compared to a reference oximeter (Vyntus CPX Pulse Oximeter) hypoxia. population sixteen healthy male subjects (mean age: 31.5 ± 7.0 years, BMI: 24.9 3.6 kg/m², 35% with darker skin tones), simultaneous RR measurements were collected over 12.4 h, which FiO2 progressively reduced from 21% 10.5%. average root mean square error (ARMS) for placed on back chest 2.94% 2.98%, respectively, permutation testing confirming ARMS below 3.5% both positions no statistically difference between patch placements. Positive correlations acceptable accuracy observed at locations (r = 0.92, p < 0.001 r 0.90, placements, respectively). Bland-Altman analysis further indicated limits agreement that support consistency across similar levels noted tones. Similar findings obtained measurements. conclusion, demonstrated robust measuring RRs hypoxia humans comparable standard hospital-grade equipment. effectiveness suggests wearable device is valuable tool RRs, potentially enhancing patient safety optimizing resource allocation. overcome study limitations allow generalized use, work larger sample, including more high phototype desaturation 80%, would be useful.

Language: Английский