Clinical Breast Cancer, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Language: Английский
Diagnostics, Journal Year: 2024, Volume and Issue: 14(14), P. 1472 - 1472
Published: July 9, 2024
With the improvement of economic conditions and increase in living standards, people's attention regard to health is also continuously increasing. They are beginning place their hopes on machines, expecting artificial intelligence (AI) provide a more humanized medical environment personalized services, thus greatly expanding supply bridging gap between resource demand. development IoT technology, arrival 5G 6G communication era, enhancement computing capabilities particular, application AI-assisted healthcare have been further promoted. Currently, research field assistance deepening expanding. AI holds immense value has many potential applications institutions, patients, professionals. It ability enhance efficiency, reduce costs, improve quality intelligent service experience for professionals patients. This study elaborates history timelines field, types technologies informatics, opportunities challenges medicine. The combination profound impact human life, improving levels life changing lifestyles.
Language: Английский
Citations
19
Nature Biotechnology, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 22, 2025
Language: Английский
Citations
5
Advanced Therapeutics, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 6, 2025
Abstract The extracellular matrix (ECM) serves not only as a structural scaffold but also an active regulator of cancer progression, profoundly influencing tumor behaviour and the microenvironment (TME). This review focuses into pivotal role ECM alterations in facilitating metastasis explores therapeutic strategies aimed at counteracting these changes. We analyse targeted interventions against collagen, including approaches to inhibit its biosynthesis disrupt associated signalling pathways critical for architecture cell migration. Additionally, therapies addressing hyaluronan are reviewed, highlighting methods suppress synthesis enzymatic degrade it, thereby mitigating tumor‐promoting effects. discussion extends innovative modulating stiffness, focusing on roles cancer‐associated fibroblasts lysyl oxidases, which key contributors remodelling mechanical signalling. By strategically modifying components, aim enhance efficacy existing treatments, tackle resistance mechanisms, achieve more durable outcomes. Insights from recent studies clinical trials highlight promise overcoming treatment improving patient Advancing our understanding biology leads development effective therapies.
Language: Английский
Citations
2
Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100132 - 100132
Published: Aug. 1, 2024
AI's potential to revolutionize oncology through enhanced diagnostics, treatment planning, and patient monitoring is well-documented globally. However, in Africa, its adoption has been slower, albeit steadily progressing. This commentary explores the integration of artificial Intelligence cancer care across assessing current state, challenges future directions. It highlights significant AI innovations such as DataPathology, PapsAI, MinoHealth, Hurone AI, which utilize for tissue analysis, cervical cell imaging, disease forecasting, remote monitoring. Despite these advancements, several impede full into African healthcare systems. Key issues include data privacy security, algorithm bias, insufficient regulatory frameworks. The review emphasizes necessity robust protection policies, representative datasets mitigate biases, clear guidelines deployment tailored context. Emerging technologies AI-enhanced telemedicine, mobile health applications, predictive analytics, virtual tumor boards, show promise overcoming geographic resource limitations. These can facilitate consultations, continuous monitoring, multidisciplinary collaborations, thereby improving accessibility outcomes. Conclusively, recommendations enhancing care, including investing infrastructure, capacity building professionals, fostering international collaborations are discussed. Addressing ethical crucial ensure responsible effective use technologies. By leveraging Africa significantly improve delivery, reduce mortality rates, enhance quality life.
Language: Английский
Citations
13
Advanced Science, Journal Year: 2025, Volume and Issue: unknown
Published: March 6, 2025
Drug repurposing identifies new therapeutic uses for the existing drugs originally developed different indications, aiming at capitalizing on established safety and efficacy profiles of known drugs. Thus, it is beneficial to bypass early stages drug development, reduction time cost associated with bringing therapies market. Traditional experimental methods are often time-consuming expensive, making artificial intelligence (AI) a promising alternative due its lower cost, computational advantages, ability uncover hidden patterns. This review focuses availability AI algorithms in their positive specific roles revealing drugs, especially being integrated virtual screening. It shown that excel analyzing large-scale datasets, identifying complicated patterns responses from these predictions potential repurposing. Building insights, challenges remain developing efficient future research, including integrating drug-related data across databases better repurposing, enhancing efficiency, advancing personalized medicine.
Language: Английский
Citations
1
ESMO Real World Data and Digital Oncology, Journal Year: 2024, Volume and Issue: 6, P. 100078 - 100078
Published: Oct. 4, 2024
Language: Английский
Citations
7
npj Precision Oncology, Journal Year: 2024, Volume and Issue: 8(1)
Published: Oct. 23, 2024
Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, compare methodological approaches outcomes. includes 34 studies. primarily evaluated on their ability answer oncologic questions across The highlights a significant variance, influenced by diverse methodologies evaluation criteria. Furthermore, differences inherent model capabilities, prompting strategies, oncological subdomains contribute heterogeneity. lack use standardized LLM-specific reporting protocols leads disparities, which must be addressed ensure comparability LLM ultimately leverage reliable integration technologies into practice.
Language: Английский
Citations
6
medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown
Published: June 13, 2024
Abstract Background Medical research with real-world clinical data can be challenging due to privacy requirements. Ideally, patient are handled in a fully pseudonymised or anonymised way. However, this make it difficult for medical researchers access and analyze large datasets exchange between hospitals. De-identifying free text is particularly the diverse documentation styles unstructured nature of data. recent advancements natural language processing (NLP), driven by development models (LLMs), have revolutionized ability extract information from text. Methods We hypothesize that LLMs highly effective tools extracting patient-related information, which subsequently used de-identify reports. To test hypothesis, we conduct benchmark study using eight locally deployable (Llama-3 8B, Llama-3 70B, Llama-2 7B, 7B “Sauerkraut”, 70B Mistral Phi-3-mini) dataset 100 letters. then remove identified our newly developed LLM-Anonymizer pipeline. Results Our results demonstrate LLM-Anonymizer, when achieved success rate 98.05% removing characters carrying personal identifying information. When evaluating performance relation number manually as containing identifiable characteristics, system missed only 1.95% erroneously redacted 0.85% characters. Conclusion provide full LLM-based Anonymizer pipeline under an open source license user-friendly web interface operates on local hardware requires no programming skills. This powerful tool has potential significantly facilitate enabling secure efficient de-identification premise, thereby addressing key challenges sharing.
Language: Английский
Citations
5
Journal of Cancer Research and Clinical Oncology, Journal Year: 2024, Volume and Issue: 150(8)
Published: Aug. 6, 2024
Abstract Triple negative breast cancer (TNBC) is most aggressive type of with multiple invasive sub-types and leading cause women’s death worldwide. Lack estrogen receptor (ER), progesterone (PR), human epidermal growth factor 2 (HER-2) causes it to spread rapidly making its treatment challenging due unresponsiveness towards anti-HER endocrine therapy. Hence, needing advanced therapeutic treatments strategies in order get better recovery from TNBC. Artificial intelligence (AI) has been emerged by giving high inputs the automated diagnosis as well several diseases, particularly AI based TNBC molecular sub-typing, become successful now days. Therefore, present review reviewed recent advancements role assistance focusing on Meanwhile, advantages, certain limitations future implications are also discussed fully understand readers regarding this issue. Graphical
Language: Английский
Citations
4
JHEP Reports, Journal Year: 2024, Volume and Issue: 6(12), P. 101209 - 101209
Published: Sept. 6, 2024
Language: Английский
Citations
4