Advances in analytics for learning and teaching, Journal Year: 2025, Volume and Issue: unknown, P. 39 - 55
Published: Jan. 1, 2025
Language: Английский
Integrative Medicine Research, Journal Year: 2024, Volume and Issue: 13(1), P. 101024 - 101024
Published: Feb. 9, 2024
The convergence of traditional, complementary, and integrative medicine (TCIM) with artificial intelligence (AI) is a promising frontier in healthcare. TCIM patient-centric approach that combines conventional complementary therapies, emphasizing holistic well-being. AI can revolutionize healthcare through data-driven decision-making personalized treatment plans. This article explores how technologies complement enhance TCIM, aligning the shared objectives researchers from both fields improving patient outcomes, enhancing care quality, promoting wellness. integration introduces exciting opportunities but also noteworthy challenges. may augment by assisting early disease detection, providing plans, predicting health trends, engagement. Challenges at intersection include data privacy security, regulatory complexities, maintaining human touch patient-provider relationships, mitigating bias algorithms. Patients' trust, informed consent, legal accountability are all essential considerations. Future directions AI-enhanced advanced medicine, understanding efficacy herbal remedies, studying interactions. Research on mitigation, acceptance, trust AI-driven crucial. In this article, we outlined merging holds great promise delivery, personalizing preventive care, Addressing challenges fostering collaboration between experts, practitioners, policymakers, however, vital to harnessing full potential integration.
Language: Английский
Citations
24
Diagnostics, Journal Year: 2023, Volume and Issue: 13(13), P. 2308 - 2308
Published: July 7, 2023
Artificial intelligence is highly regarded as the most promising future technology that will have a great impact on healthcare across all specialties. Its subsets, machine learning, deep and artificial neural networks, are able to automatically learn from massive amounts of data can improve prediction algorithms enhance their performance. This area still under development, but latest evidence shows potential in diagnosis, prognosis, treatment urological diseases, including bladder cancer, which currently using old tools historical nomograms. review focuses significant comprehensive literature management cancer investigates near introduction clinical practice.
Language: Английский
Citations
30
Current Oncology, Journal Year: 2023, Volume and Issue: 30(3), P. 3432 - 3446
Published: March 16, 2023
Cancer significantly contributes to global mortality, with 9.3 million annual deaths. To alleviate this burden, the utilization of artificial intelligence (AI) applications has been proposed in various domains oncology. However, potential AI and barriers its widespread adoption remain unclear. This study aimed address gap by conducting a cross-sectional, global, web-based survey over 1000 cancer researchers. The results indicated that most respondents believed would positively impact grading classification, follow-up services, diagnostic accuracy. Despite these benefits, several limitations were identified, including difficulties incorporating into clinical practice lack standardization health data. These pose significant challenges, particularly regarding testing, validation, certification, auditing algorithms systems. provide valuable insights for informed decision-making stakeholders involved research development, individual researchers funding agencies.
Language: Английский
Citations
27
Multicultural Islamic Education Review, Journal Year: 2023, Volume and Issue: 1(2), P. 109 - 179
Published: Dec. 8, 2023
In Digital Literacy 5.0, the intersectionality of digital competence across various domains marks a paradigm shift from traditional siloed approaches to more integrated and holistic framework. This article explores pervasive influence literacy diverse fields including health, medicine, nutrition, medical tourism, economy, biomedical sciences, bioinformatics, telemedicine, telehealth, artificial intelligence (AI), vascular surgery. Emphasizing necessity not just as skill for tool utilization but cornerstone understanding leveraging potential technologies, this comprehensive exploration underscores critical role in enhancing patient outcomes, driving economic growth, spurring innovation, revolutionizing healthcare surgical practices. Through multidisciplinary lens, elucidates indispensability technologically interconnected era, highlighting its implications policy, educational paradigms, future technological advancements.
Language: Английский
Citations
27
Applied Sciences, Journal Year: 2024, Volume and Issue: 14(2), P. 923 - 923
Published: Jan. 22, 2024
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing segmentation, focusing on lung CT scan chest X-ray datasets. Best-cost values reveal PSO algorithm’s performance, HE demonstrating significant stabilization enhanced convergence, particularly complex images. Evaluation metrics, including accuracy, precision, recall, F1-score/Dice, specificity, Jaccard, show substantial improvements preprocessing, emphasizing its impact accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, K-means, confirm competitiveness PSO-HE approach, especially The also underscores positive influence clarity precision. These findings highlight promise approach advancing accuracy reliability pave way further method integration to enhance this critical healthcare application.
Language: Английский
Citations
10
Current Opinion in Urology, Journal Year: 2025, Volume and Issue: unknown
Published: March 3, 2025
Purpose of review By leveraging models such as large language (LLMs) and generative computer vision tools, artificial intelligence (GAI) is reshaping cancer research oncologic practice from diagnosis to treatment follow-up. This timely provides a comprehensive overview the current applications future potential GAI in oncology, including urologic malignancies. Recent findings has demonstrated significant improving by integrating multimodal data, diagnostic workflows, assisting imaging interpretation. In treatment, shows promise aligning clinical decisions with guidelines, optimizing systemic therapy choices, aiding patient education. Posttreatment, include streamlining administrative tasks, follow-up care, monitoring adverse events. image analysis, data extraction, outcomes research. Future developments could stimulate discovery, improve efficiency, enhance patient-physician relationship. Summary Integration into oncology shown some ability accuracy, optimize decisions, ultimately strengthening Despite these advancements, inherent stochasticity GAI's performance necessitates human oversight, more specialized models, proper physician training, robust guidelines ensure its well tolerated effective integration practice.
Language: Английский
Citations
1
European Radiology, Journal Year: 2023, Volume and Issue: 34(1), P. 391 - 399
Published: Aug. 8, 2023
Language: Английский
Citations
22
Public Health Nursing, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 4, 2024
ABSTRACT Background Artificial intelligence now encompasses technologies like machine learning, natural language processing, and robotics, allowing machines to undertake complex tasks traditionally done by humans. AI's application in healthcare has led advancements diagnostic tools, predictive analytics, surgical precision. Aim This comprehensive review aims explore the transformative impact of AI across diverse domains, highlighting its applications, advancements, challenges, contributions enhancing patient care. Methodology A literature search was conducted multiple databases, covering publications from 2014 2024. Keywords related applications were used gather data, focusing on studies exploring role medical specialties. Results demonstrated substantial benefits various fields medicine. In cardiology, it aids automated image interpretation, risk prediction, management cardiovascular diseases. oncology, enhances cancer detection, treatment planning, personalized drug selection. Radiology improved analysis accuracy, while critical care sees triage resource optimization. integration into pediatrics, surgery, public health, neurology, pathology, mental health similarly shown significant improvements precision, treatment, overall The implementation low‐resource settings been particularly impactful, access advanced tools treatments. Conclusion is rapidly changing industry greatly increasing accuracy diagnoses, streamlining plans, improving outcomes a variety specializations. underscores potential, early disease detection ability augment delivery, resource‐limited settings.
Language: Английский
Citations
8
International Journal of Cancer, Journal Year: 2024, Volume and Issue: 155(1), P. 139 - 148
Published: March 7, 2024
Abstract Management of colon cancer has changed over the last few decades. We assessed trends in management and outcomes using US National Cancer Database (NCDB). A retrospective analysis all patients with colonic adenocarcinoma between 2005 2019 was conducted. The cohort divided into three equal time periods: Period 1 (2005–2009), 2 (2010–2014), 3 (2015–2019) to examine treatment trends. primary outcome 5‐year overall survival (OS). study included 923,275 patients. significant increase stage IV disease noted compared (47.9% vs. 27.9%, respectively), whereas a reciprocal reduction seen locally advanced (stage II: 20.8%–12%; III: 14.5%–7.7%). Use immunotherapy significantly increased from 0.3% 7.6%. Mean OS (43.6 42.1 months) despite metastatic longer diagnosis definitive surgery (7 14 days). 30‐day readmission (5.1%–4.2%), 30‐ (3.9%–2.8%), 90‐day mortality (7.1%–5%) seen. Laparoscopic robotic 45.8% 53.1% 2.9% 12.7%, respectively. Median postoperative length hospital stay decreased by days. Rate positive resection margins (7.2%–6%) median number examined lymph nodes (14–16) also improved. Minimally invasive for recent years. Patient including improved time.
Language: Английский
Citations
7
Exploration of Targeted Anti-tumor Therapy, Journal Year: 2022, Volume and Issue: unknown, P. 795 - 816
Published: Dec. 27, 2022
The advent of artificial intelligence (AI) represents a real game changer in today's landscape breast cancer imaging. Several innovative AI-based tools have been developed and validated recent years that promise to accelerate the goal patient-tailored management. Numerous studies confirm proper integration AI into existing clinical workflows could bring significant benefits women, radiologists, healthcare systems. approach has proved particularly useful for developing new risk prediction models integrate multi-data streams planning individualized screening protocols. Furthermore, help radiologists pre-screening lesion detection phase, increasing diagnostic accuracy, while reducing workload complications related overdiagnosis. Radiomics radiogenomics approaches extrapolate so-called imaging signature tumor plan targeted treatment. main challenges development are huge amounts high-quality data required train validate these need multidisciplinary team with solid machine-learning skills. purpose this article is present summary most important applications imaging, analyzing possible perspectives widespread adoption tools.
Language: Английский
Citations
25