Neural Networks, Journal Year: 2025, Volume and Issue: 188, P. 107504 - 107504
Published: April 29, 2025
Language: Английский
Current Research in Biotechnology, Journal Year: 2023, Volume and Issue: 7, P. 100164 - 100164
Published: Nov. 22, 2023
The medicine and healthcare sector has been evolving advancing very fast. advancement initiated shaped by the applications of data-driven, robust, efficient machine learning (ML) to deep (DL) technologies. ML in medical is developing quickly, causing rapid progress, reshaping medicine, improving clinician patient experiences. technologies evolved into data-hungry DL approaches, which are more robust dealing with data. This article reviews some critical data-driven aspects intelligence field. In this direction, illustrated recent progress science using two categories: firstly, development data uses and, secondly, Chabot particularly on ChatGPT. Here, we discuss ML, DL, transition requirements from DL. To science, illustrate prospective studies image data, newly interpretation EMR or EHR, big personalized dataset shifts artificial (AI). Simultaneously, recently developed DL-enabled ChatGPT technology. Finally, summarize broad role significant challenges for implementing healthcare. overview paradigm shift will benefit researchers immensely.
Language: Английский
Citations
67
Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)
Published: March 15, 2024
Abstract The purpose of this research is to identify and evaluate the technical, ethical regulatory challenges related use Artificial Intelligence (AI) in healthcare. potential applications AI healthcare seem limitless vary their nature scope, ranging from privacy, research, informed consent, patient autonomy, accountability, health equity, fairness, AI-based diagnostic algorithms care management through automation for specific manual activities reduce paperwork human error. main faced by states regulating were identified, especially legal voids complexities adequate regulation better transparency. A few recommendations made protect data, mitigate risks regulate more efficiently international cooperation adoption harmonized standards under World Health Organization (WHO) line with its constitutional mandate digital public health. European Union (EU) law can serve as a model guidance WHO reform International Regulations (IHR).
Language: Английский
Citations
26
Antibiotics, Journal Year: 2024, Volume and Issue: 13(6), P. 502 - 502
Published: May 29, 2024
Antibiotic resistance poses a significant threat to global public health due complex interactions between bacterial genetic factors and external influences such as antibiotic misuse. Artificial intelligence (AI) offers innovative strategies address this crisis. For example, AI can analyze genomic data detect markers early on, enabling interventions. In addition, AI-powered decision support systems optimize use by recommending the most effective treatments based on patient local patterns. accelerate drug discovery predicting efficacy of new compounds identifying potential antibacterial agents. Although progress has been made, challenges persist, including quality, model interpretability, real-world implementation. A multidisciplinary approach that integrates with other emerging technologies, synthetic biology nanomedicine, could pave way for prevention mitigation antimicrobial resistance, preserving antibiotics future generations.
Language: Английский
Citations
21
British Journal of Biomedical Science, Journal Year: 2025, Volume and Issue: 81
Published: Jan. 9, 2025
Generative Artificial Intelligence (GenAI) is rapidly transforming the landscape of higher education, offering novel opportunities for personalised learning and innovative assessment methods. This paper explores dual-edged nature GenAI's integration into educational practices, focusing on both its potential to enhance student engagement outcomes significant challenges it poses academic integrity equity. Through a comprehensive review current literature, we examine implications GenAI highlighting need robust ethical frameworks guide use. Our analysis framed within pedagogical theories, including social constructivism competency-based learning, importance balancing human expertise AI capabilities. We also address broader concerns associated with GenAI, such as risks bias, digital divide, environmental impact technologies. argues that while can provide substantial benefits in terms automation efficiency, must be managed care avoid undermining authenticity work exacerbating existing inequalities. Finally, propose set recommendations institutions, developing literacy programmes, revising designs incorporate critical thinking creativity, establishing transparent policies ensure fairness accountability By fostering responsible approach education harness safeguarding core values inclusive education.
Language: Английский
Citations
5
Neural Networks, Journal Year: 2025, Volume and Issue: 184, P. 107088 - 107088
Published: Jan. 2, 2025
Language: Английский
Citations
2
Journal of Petroleum Exploration and Production Technology, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 1, 2025
Language: Английский
Citations
1
Biofabrication, Journal Year: 2024, Volume and Issue: 16(4), P. 045014 - 045014
Published: July 15, 2024
Abstract 3D (Bio)printing is a highly effective method for fabricating tissue engineering scaffolds, renowned their exceptional precision and control. Artificial intelligence (AI) has become crucial technology in this field, capable of learning replicating complex patterns that surpass human capabilities. However, the integration AI often hampered by lack comprehensive reliable data. This study addresses these challenges providing one most extensive datasets on 3D-printed scaffolds. It provides open-source dataset employs various techniques, from unsupervised to supervised learning. includes detailed information 1171 featuring variety biomaterials concentrations—including 60 such as natural synthesized biomaterials, crosslinkers, enzymes, etc.—along with 49 cell lines, densities, different printing conditions. We used over 40 machine deep algorithms, tuning hyperparameters reveal hidden predict response, printability, scaffold quality. The clustering analysis using KMeans identified five distinct ones. In classification tasks, algorithms XGBoost, Gradient Boosting, Extra Trees Classifier, Random Forest LightGBM demonstrated superior performance, achieving higher accuracy F1 scores. A fully connected neural network six layers scratch was developed, precisely its accurate predictions. developed associated code are publicly available https://github.com/saeedrafieyan/MLATE promote future research.
Language: Английский
Citations
9
Human Gene, Journal Year: 2024, Volume and Issue: 41, P. 201297 - 201297
Published: May 22, 2024
Language: Английский
Citations
8
International Journal of Biology and Pharmacy Research Updates, Journal Year: 2024, Volume and Issue: 3(2), P. 01 - 010
Published: April 13, 2024
In recent years, the convergence of healthcare and big data analytics has opened new avenues for tailored health communication, enabling personalized interventions improving outcomes. This systematic review investigates impact techniques harnessing communication. The synthesizes findings from diverse studies spanning sectors, including public campaigns, clinical interventions, patient engagement initiatives. It examines effectiveness communication strategies in addressing various challenges, such as chronic diseases, infectious outbreaks, mental disorders. Key highlight significant positive on behavior change, treatment adherence, empowerment. Big enable segmentation populations based socio-demographic, behavioral, characteristics, facilitating delivery targeted messages to individual preferences needs. Personalization enhances engagement, fosters trust, motivates individuals adopt healthier lifestyles adhere medical recommendations. Furthermore, explores technologies employed Machine learning algorithms, natural language processing, predictive modeling are leveraged analyze vast datasets, predict outcomes, tailor real-time. Mobile applications, social media platforms, wearable devices serve channels delivering collecting real-time data. However, also identifies challenges limitations, privacy concerns, security risks, digital divide. Ethical considerations regarding collection, consent, transparency paramount ensuring responsible use underscores transformative potential By leveraging advanced technology, stakeholders can deliver that resonate with individuals, ultimately driving change outcomes a population scale.
Language: Английский
Citations
7
Published: Feb. 9, 2024
The intelligent revisiting of ROC Curves for complex function extraction in AI-primarily based lung cancer prediction involves the application numerous advanced synthetic Intelligence (AI) models and techniques extracting visualizing valuable functions from clinical imaging data. visualization features medical data are necessities diagnostics predictions. utilizes identification great morphological characteristics most cells, which commonly represented by ROIs (areas hobby). To efficiently diagnose cancerous formations, AI fashions utilize extracted to assemble a (Receiver running characteristic) curve. curves widely used evaluate accuracy given version while detecting cells.
Language: Английский
Citations
6