Results 51 to 60 of about 65,281 (258)

Reconfigurable Au Nanoparticle Monolayers on Regenerated Cellulose Hydrogels: Highly Sensitive SERS Detection of Polystyrene Micro/Nanoplastics With Interpretable Deep Learning

Advanced Functional Materials, EarlyView.
A regenerated cellulose (RC) hydrogel‐based SERS substrate integrating a Marangoni‐transferred gold nanoparticle self‐assembled monolayer (Au‐SAM) is fabricated. Reswelling‐induced hotspot formation enhances polystyrene micro/nanoplastics (PS MNPs) detection in complex matrices, providing reproducible, high‐throughput SERS signals across diverse ...
Youngho Jeon, Yu‐Jin Jeon, Suji Lee, Jeseong Kim, Dae‐Hyun Jung, Jungmok You   +5 more
wiley   +1 more source

Evaluation of deep learning tools in medical diagnosis and treatment of cancer: research analysis of clinical and randomized clinical trials

Frontiers in Network Physiology
Artificial Intelligence and machine learning tools have brought a revolution in the healthcare sector. This has allowed healthcare providers, patients, and public to be at pole position -amidst the key consideration and barriers-to attain precision and ...
Rawad Hodeify
doaj   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Disease diagnosis and prediction using deep learning: a review [PDF]

PeerJ Computer Science
Deep learning (DL) is a machine learning technique that processes data in a manner influenced by the functioning of the human brain. It is an effective tool for deciphering complicated data and may be applied to many other processes, such as decision ...
Shyamala Krishnan, Navamani Thandava Meganathan   +1 more
doaj   +2 more sources

DL-Scale: Deep Learning for model upgrading in topology optimization

Procedia Manufacturing, 2020
Abstract Topology optimization is used for defining the optimal arrangement of material within a specific domain with respect to transferring specific loads to predetermined supports in the best possible way. Deep learning techniques have achieved significant results in computer vision [1], natural language processing [1], big-data management [2 ...
Nikos Ath. Kallioras, Nikos D. Lagaros
openaire   +1 more source

Stability of Medicinal Nanoemulsions to Spaceflight: Insights From the StarMed Experiment

Advanced Healthcare Materials, EarlyView.
Chitosan‐coated melatonin nanoemulsions (MN) recovered from a sounding rocket mission preserve droplet size and controlled‐release behavior, whereas uncoated nanoemulsions show ageing‐driven droplet growth and increased accessible drug fraction. Simple polymer coatings thus enhance the flight resilience of liquid space medicines under cumulative launch
Modupe Adebowale, Nguyen Van Duc Long, Philip M. Williams, Jens Hauslage, Volker Hessel   +4 more
wiley   +1 more source

Application of Deep Learning in Cancer Prognosis Prediction Model

Technology in Cancer Research & Treatment, 2023
As an important branch of artificial intelligence and machine learning, deep learning (DL) has been widely used in various aspects of cancer auxiliary diagnosis, among which cancer prognosis is the most important part.
Heng Zhang MS, Qianyi Xi MS, Fan Zhang MS, Qixuan Li MS, Zhuqing Jiao PhD, Xinye Ni PhD   +5 more
doaj   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Integrating CT-based radiomics and deep learning for invasive prediction of ground-glass nodules in lung adenocarcinoma: a multicohort study

Insights into Imaging
Objectives This study aimed to explore a multiple-instance learning (MIL) framework incorporating radiomics features and deep learning representations to predict the invasiveness of ground-glass nodules (GGNs) in lung adenocarcinoma (LUAD) using ...
Hai Du, Jing Shen, Feng Chen, Kaifeng Wang, Lili Qin, Yijiang Hu, Yue Xiao, Xiulin Wang, Jianlin Wu   +8 more
doaj   +1 more source