Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 107 - 145
Published: Nov. 8, 2024
Language: Английский
Cancer Management and Research, Journal Year: 2024, Volume and Issue: Volume 16, P. 1389 - 1403
Published: Oct. 1, 2024
Abstract: Colorectal cancer (CRC) is a diverse disease entity and leading cause of cancer-related mortality worldwide. CRC results from the accumulation multiple genetic epigenetic alterations. This heterogeneity underscores significance understanding its molecular landscape, as variations in tumor genetics can greatly influence both patient prognosis therapeutic response. The complexity defined by three major carcinogenesis pathways: chromosomal instability (CIN), microsatellite (MSI), CpG island methylator phenotype (CIMP). These pathways contribute to onset progression through mutations, modifications, dysregulated cellular signalling networks. heterogeneous nature continues pose challenges identifying universally effective treatments, highlighting need for personalized approaches. Hence, present review aims at unravelling that essential improving diagnosis, prognostication, treatment. We detail on current framework CRC, central associated with initiation malignant phenotype, further invasion, progression, metastases, response therapy. Continued research into CRC's biomarkers will pave way development more precise strategies, ultimately outcomes. Keywords: colorectal cancer, mechanisms, pathways, instability, adenomatous polyposis coli,
Language: Английский
Citations
8
Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15
Published: Feb. 4, 2025
Background Artificial intelligence (AI) has emerged as a transformative tool in oncology, offering promising applications chemotherapy development, cancer diagnosis, and predicting response. Despite its potential, debates persist regarding the predictive accuracy of AI technologies, particularly machine learning (ML) deep (DL). Objective This review aims to explore role forecasting outcomes related treatment response, synthesizing current advancements identifying critical gaps field. Methods A comprehensive literature search was conducted across PubMed, Embase, Web Science, Cochrane databases up 2023. Keywords included “Artificial Intelligence (AI),” “Machine Learning (ML),” “Deep (DL)” combined with “chemotherapy development,” “cancer diagnosis,” treatment.” Articles published within last four years written English were included. The Prediction Model Risk Bias Assessment utilized assess risk bias selected studies. Conclusion underscores substantial impact AI, including ML DL, on innovation, response for both solid hematological tumors. Evidence from recent studies highlights AI’s potential reduce cancer-related mortality by optimizing diagnostic accuracy, personalizing plans, improving therapeutic outcomes. Future research should focus addressing challenges clinical implementation, ethical considerations, scalability enhance integration into oncology care.
Language: Английский
Citations
1
Pharmaceutical Research, Journal Year: 2024, Volume and Issue: 41(4), P. 721 - 730
Published: March 5, 2024
Language: Английский
Citations
6
Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 175 - 199
Published: Jan. 1, 2025
Language: Английский
Citations
0
Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(7), P. 2255 - 2255
Published: March 26, 2025
Background/Objectives: The management of locally advanced rectal cancer has evolved significantly, shaped by advances in multimodal neoadjuvant therapy and a growing emphasis on organ preservation through the watch-and-wait approach. These advancements, however, introduce complex treatment decisions that require careful consideration both patients clinicians. Methods: This narrative review explores evolution role shared decision-making guiding decisions, particularly for facing between surgical resection watch-and-wait. Additionally, it discusses development tools to aid shared-decision making, current challenges implementing future directions improvement patient centered care management. Results: Considerations decision making include anatomical considerations influence options, potential benefits risks versus rectum, impact bowel, urinary, sexual function. must weigh long-term implications their choices quality life. Conclusions: Shared emerged as critical component patient-centered ensures align with patients' values priorities. Given preference-sensitive nature cancer, plays an important helping navigate these decisions.
Language: Английский
Citations
0
Asian Journal of Research in Computer Science, Journal Year: 2024, Volume and Issue: 17(7), P. 103 - 118
Published: July 4, 2024
Testing the security, efficiency, and dependability of AI-driven healthcare systems is crucial. It essential to perform thorough rigorous testing make sure AI algorithms are capable. Our goal ensure that these can handle a wide range scenarios may occur in settings. We must observe, for instance, how well they function presence changes patient characteristics, data accuracy, even environmental factors. Developers able go deeply find any potential flaws, biases, or restrictions by thoroughly models. This enables them enhance maximize algorithms' performance. be adaptable strong, ready overcome challenges. robust, whatever challenges encounter. Reliability another crucial step this process. guarantee that, over time, predictions actual medical contexts continue accurate dependable. In end, we rely on produce trustworthy outcomes actually care. institutions not only parties involved this. Policymakers regulatory bodies also quite important. They put lot effort into developing standards protocols carrying out demanding field. Strict safety efficacy met solutions thanks requirements set procedures, quality, performance indicators. article focuses all current robustness reliability using Healthcare.
Language: Английский
Citations
2
Journal of Surgical Oncology, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 9, 2024
ABSTRACT A considerable amount of recent research has focused on the role artificial intelligence (AI) in colorectal cancer (CRC), aiming to improve outcomes CRC. However, AI for young onset (yoCRC)—defined as patients less than 50 years old—is not nearly explored, and its prevention, detection, management yoCRC remains largely unknown. To address this gap, we performed an integrative review yoCRC. We conducted a comprehensive literature search PubMed, Medline (Ovid), Embase articles published from 2020 2024, adhering specific inclusion exclusion criteria. This involved gathering information diverse designs sources. After removing duplicates applying criteria, total 11 were included review. Our analysis identified one discussing importance yoCRC, three presenting studies mentioning applications seven investigations utilizing with focus The findings indicate that while CRC is evolving field, there are few plans or implementations reported how incorporate specifically Potential limitations include limited number databases searched scope queries used. Nonetheless, highlights need more targeted Future can build upon foundation adjustments account increasing incidence
Language: Английский
Citations
1
Diagnostics, Journal Year: 2024, Volume and Issue: 14(18), P. 2074 - 2074
Published: Sept. 19, 2024
Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model identify and predict which subset of colorectal cancer patients are more likely experience chemotherapy-induced toxicity determine specific attributes that influence presence treatment-related side effects.
Language: Английский
Citations
0
Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 323 - 347
Published: Nov. 8, 2024
Citations
0
Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 107 - 145
Published: Nov. 8, 2024
Language: Английский
Citations
0