Software and hardware co-design of AI high-rate chips for parallel training of edge intelligence DOI
Haiqiang Li, Zhixin Ling, Chaoyi Yang

et al.

Intelligent Decision Technologies, Journal Year: 2024, Volume and Issue: 18(4), P. 3259 - 3276

Published: Nov. 1, 2024

With the digital transformation of information technology and industry, applicability scenarios edge intelligent terminals are expanding. AI chips have become one mainstream core devices terminals. How to select suitable according application through systematic analysis has an urgent problem be solved. This paper first provides a comparative technical architecture advantages disadvantages chips; then proposes low implementation complexity, multi-code rate fusion LDPC parallel coding structure, encoder chip design scheme using this structure for high-speed transmission applications. Based on TSMC 130 nm CMOS standard cell library, can achieve throughput 1.6 Gbps at 200 MHz clock consume only 184.3 m W. Compared with same designed in conventional architecture, solution reduce storage space requirement 18.52% architecture. The proposed encoding not maintains high performance but also significantly reduces demand space, making it good choice resource-constrained environments.

Language: Английский

Research Trends and Dynamics in Single-cell RNA Sequencing for Musculoskeletal Diseases: A Scientometric and Visualization Study DOI Creative Commons
Siyang Cao, Yihao Wei, Yaohang Yue

et al.

International Journal of Medical Sciences, Journal Year: 2025, Volume and Issue: 22(3), P. 528 - 550

Published: Jan. 1, 2025

Background: Worldwide, approximately 1.7 billion people are afflicted with musculoskeletal (MSK) diseases, posing significant health challenges. The introduction of single-cell RNA sequencing (scRNA-seq) technology provides novel insights and approaches to comprehend the onset, progression, treatment MSK diseases. Nevertheless, there is a remarkable lack analytical descriptive studies regarding trajectory, essential research directions, current situation, pivotal focuses, upcoming perspectives. Therefore, aim this present comprehensive overview advancements made in scRNA-seq for disorders over past 15 years. Methods: It utilizes robust dataset derived from Web Science Core Collection, encompassing January 1, 2009, through September 6, 2024. To achieve this, advanced methodologies were applied conduct thorough scientometric visual analyses. Results: findings underscore preeminent role China, which contributes 63.49% total publications, thereby exerting substantial impact within domain. Notable contributions came institutions such as Shanghai Jiao Tong University, Sun Yat-sen Harvard Medical School, Liu Yun being leading contributor. Frontiers Immunology published greatest number papers field. This study identified joint bone neoplasms, fractures, intervertebral disc degeneration main focuses. Conclusion: extensive analysis benefits both experienced novice researchers by facilitating immediate access critical data, fostering innovation

Language: Английский

Citations

3
Impact of Metabolites from Foodborne Pathogens on Cancer DOI Creative Commons
Alice Njolke Mafe, Dietrich Büsselberg

Foods, Journal Year: 2024, Volume and Issue: 13(23), P. 3886 - 3886

Published: Dec. 1, 2024

Foodborne pathogens are microorganisms that cause illness through contamination, presenting significant risks to public health and food safety. This review explores the metabolites produced by these pathogens, including toxins secondary metabolites, their implications for human health, particularly concerning cancer risk. We examine various such as Salmonella sp., Campylobacter Escherichia coli, Listeria monocytogenes, detailing specific of concern carcinogenic mechanisms. study discusses analytical techniques detecting chromatography, spectrometry, immunoassays, along with challenges associated detection. covers effective control strategies, processing techniques, sanitation practices, regulatory measures, emerging technologies in pathogen control. manuscript considers broader highlighting importance robust policies, awareness, education. identifies research gaps innovative approaches, recommending advancements detection methods, preventive policy improvements better manage foodborne metabolites.

Language: Английский

Citations

11
Wearable Aptasensors DOI
Navid Rabiee, Mohammad Rabiee

Analytical Chemistry, Journal Year: 2024, Volume and Issue: 96(49), P. 19160 - 19182

Published: Nov. 27, 2024

This Perspective explores the revolutionary advances in wearable aptasensor (WA) technology, which combines devices and aptamer-based detection systems for personalized, real-time health monitoring. The leverage specificity sensitivity of aptamers to target specific molecules, offering broad applications from continuous glucose tracking early diagnosis diseases. integration data analytics artificial intelligence (AI) allows risk prediction guides preventive measures. While challenges miniaturization, power efficiency, security persist, these hold significant potential democratize healthcare reshape patient-doctor interactions.

Language: Английский

Citations

6
Editorial Perspective: Advancements in Microfluidics and Biochip Technologies DOI Creative Commons
Hyunil Ryu, Tae‐Joon Jeon, Sun Min Kim

et al.

Micromachines, Journal Year: 2025, Volume and Issue: 16(1), P. 77 - 77

Published: Jan. 11, 2025

Microfluidics and biochip technologies continue to play a key role in driving innovation across biomedical, environmental engineering disciplines [...]

Language: Английский

Citations

0
Unraveling the future: hot topics shaping molecular diagnostics Today DOI Creative Commons
Sabine Weiskirchen, Ralf Weiskirchen

Expert Review of Molecular Diagnostics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 16, 2025

This special report highlights the transformative potential of advanced diagnostic technologies in modern healthcare, emphasizing their role enhancing disease detection, treatment personalization, and patient outcomes. Innovations such as Next-Generation Sequencing (NGS), liquid biopsy, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) -based diagnostics, Point-of-Care (PoC) testing, microbiome analysis, Artificial Intelligence are reshaping landscape. These methods facilitate early identification diseases, enable tailored therapies based on individual genetic profiles, provide noninvasive monitoring options. Furthermore, telemedicine enhances access to care while reducing costs associated with traditional healthcare delivery. Despite these advancements, challenges remain regarding regulatory compliance, data privacy concerns, disparities services. The underscores need for ongoing collaboration among stakeholders address limitations effectively. By prioritizing equitable continuously evaluating emerging technologies' impact safety health outcomes, system can harness full diagnostics improve global health.

Language: Английский

Citations

0
Harnessing artificial intelligence for theragnostic applications: Current landscape and future directions DOI

Arundhati Pande,

Abhishek Kumar, Ashish Anjankar

et al.

Multidisciplinary Reviews, Journal Year: 2025, Volume and Issue: 8(7), P. 2025218 - 2025218

Published: Feb. 7, 2025

In the area of theragnostics, use artificial intelligence (AI) is supporting personalised medicine methods that merge therapeutic and diagnostic techniques, which causing sector to undergo a transition. An analysis historical backdrop, current condition, promise intelligence-enhanced theragnostic systems presented in this article. We investigate underlying ideas intelligence, such as machine learning, deep neural networks, well their applications variety medical fields, including cancer, pathology, imaging, cardiology, hypertension control, diabetes management. The ability integrate wide information, recognise trends, enable real-time decision-making patient monitoring all illustrate competency. It possible digital twins, make adaptive learning algorithms dynamic virtual models, might be used optimise treatment regimens anticipate course illness. Important prospects for advancement biomedical research therapy are by biochip technology driven intelligence. This includes gene chips, organ-on-a-chip systems, biosensors. However, there number obstacles must overcome before can effectively theragnostics. These include data security, privacy, algorithmic biases, legal frameworks, acceptability. vital, order realise full potential AI-driven address these constraints means extensive validation, diversified datasets, explainable clear communication. anticipated synergistic combination theragnostics will revolutionise precision continues advance. it more accurate diagnoses, achieve tailored therapeutics, better outcomes.

Language: Английский

Citations

0
Machine learning and clinical EEG data for multiple sclerosis: A systematic review DOI Creative Commons

Badr Mouazen,

Ahmed Bendaouia, El Hassan Abdelwahed

et al.

Artificial Intelligence in Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 103116 - 103116

Published: April 1, 2025

Language: Английский

Citations

0
A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry DOI

Jaleh Bagheri Hamzyan Olia,

Arasu Raman, Chou‐Yi Hsu

et al.

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 189, P. 109984 - 109984

Published: March 14, 2025

Language: Английский

Citations

0
Software and hardware co-design of AI high-rate chips for parallel training of edge intelligence DOI
Haiqiang Li, Zhixin Ling, Chaoyi Yang

et al.

Intelligent Decision Technologies, Journal Year: 2024, Volume and Issue: 18(4), P. 3259 - 3276

Published: Nov. 1, 2024

With the digital transformation of information technology and industry, applicability scenarios edge intelligent terminals are expanding. AI chips have become one mainstream core devices terminals. How to select suitable according application through systematic analysis has an urgent problem be solved. This paper first provides a comparative technical architecture advantages disadvantages chips; then proposes low implementation complexity, multi-code rate fusion LDPC parallel coding structure, encoder chip design scheme using this structure for high-speed transmission applications. Based on TSMC 130 nm CMOS standard cell library, can achieve throughput 1.6 Gbps at 200 MHz clock consume only 184.3 m W. Compared with same designed in conventional architecture, solution reduce storage space requirement 18.52% architecture. The proposed encoding not maintains high performance but also significantly reduces demand space, making it good choice resource-constrained environments.

Language: Английский

Citations

0