Results 81 to 90 of about 84,699 (302)

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

Early-Stage Alzheimer's Disease Detection Using an Explainable Deep Learning Method and Functional Magnetic Resonance Imaging (fMRI)

, 2023
reservedAlzheimer’s disease (AD) is a degenerative condition that alters the brain’s biology and structural integrity. Degeneration can lead to memory loss and social and cognitive deterioration. An individual’s death might happen depending on how severe
EBRAHIMIAN BABOUKANI, REZA
core  

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

Advanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee, Moon‐Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son, Munwon Lim, Minho Kang, Dong Yun Lee, Donghyun Lim, Jung‐Hoon Park, Gi Doo Cha, Soo‐Hong Lee, Tae‐Sik Jang, Kisuk Yang, Yunho Jeong, Youngho Eom, Hyun‐Do Jung   +21 more
wiley   +1 more source

A Modular Deep Learning Pipeline for Cell Culture Analysis: Investigating the Proliferation of Cardiomyocytes

, 2023
760773Cardiovascular disease is a leading cause of death in the Western world. The exploration of strategies to enhance the regenerative capacity of the mammalian heart is therefore of great interest.
Haas, Julius, Fleischmann, Bernd, Hesse, Michael, Becker, Cora, Frye, Maik, Leyendecker, Lars, Piotrowski, Tobias, Schmitt, Robert H.   +7 more
core  

An overview of deep-learning models for metasurface design and optimization

, 2023
Deep Neural Networks (DNNs) have emerged as a powerful tool for predicting the structure and composition of diverse nanophotonic devices based on their desired response.
Mehmood, Muhammad Qasim, Massoud, Yehia Mahmoud, Fizan, Muhammad, Noureen, Sadia, Zubair, Muhammad   +4 more
core   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 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

Deep Learning-Based Predictive Control of Vehicle-to-Grid Onboard Charger Back Stage Models

IEEE Access
To address the insufficient modeling accuracy and slow dynamic response of the Capacitor-Inductor-Inductor-Capacitor (CLLC) resonant converter in Vehicle-to-Grid (V2G) automotive onboard charger, a deep learning-based model predictive control method for ...
Yongquan Zhang, Weidong Xue, Shuaibing Li, Yongqiang Kang, Junmin Zhu, Haiying Dong   +5 more
doaj   +1 more source

At Home Detection of Ovarian Health Biomarker in Menstruation Blood

Advanced Materials Technologies, EarlyView.
A lateral flow assay enables the detection of anti‐Müllerian hormone directly in unprocessed menstrual blood using silica‐gold nanoshells and smartphone‐assisted machine learning analysis. The platform supports decentralized, user‐operated testing in wearable and dipstick formats, highlighting the potential of menstrual blood as a non‐invasive matrix ...
Lucas Dosnon, Thomas Rduch, Salma Sherif Azer, Inge K. Herrmann   +3 more
wiley   +1 more source

A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications

Information
Deep learning (DL) has become a core component of modern artificial intelligence (AI), driving significant advancements across diverse fields by facilitating the analysis of complex systems, from protein folding in biology to molecular discovery in ...
Ibomoiye Domor Mienye, Theo G. Swart
doaj   +1 more source