Results 231 to 240 of about 52,085 (312)

Automated and accurate view classification of fetal echocardiography using convolutional neural networks. [PDF]

Quant Imaging Med Surg
Shi J, Bai Y, Hou Q, He S, Hong L, Cui L, Zhang Y, Liu T, Deng W, Liu J, Ma J, Xiao S, Wang Z, Yang Y, Zhang L, Cao H, Xie M, Wang J.   +17 more
europepmc   +1 more source

Cellpose+, a Morphological Analysis Tool for Feature Extraction of Stained Cell Images

Advanced Intelligent Discovery, EarlyView.
We introduce Cellpose plus, a morphological and geometrical analysis tool for feature extraction of stained cell images built over Cellpose, a state‐of‐the‐art cell segmentation framework. We also introduce a dataset of DAPI and FITC stained cells to which our new method is applied.
Israel A. Huaman, Fares D. E. Ghorabe, Sofya S. Chumakova, Alexandra A. Pisarenko, Alexey E. Dudaev, Tatiana G. Volova, Galina A. Ryltseva, Sviatlana A. Ulasevich, Ekaterina I. Shishatskaya, Ekaterina V. Skorb, Pavel S. Zun   +10 more
wiley   +1 more source

An ensemble heterogeneous transformer model for an effective diagnosis of multiple plant diseases. [PDF]

Front Plant Sci
Kalpana P, Gera P, Alabdulkreem E, Quasim MT, Baili J, Cho Y, Nam Y.   +6 more
europepmc   +1 more source

AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing

Advanced Intelligent Discovery, EarlyView.
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley   +1 more source

Computer-aided diagnosis of Haematologic disorders detection based on spatial feature learning networks using blood cell images. [PDF]

Sci Rep
Alsamri J, Alqahtani H, Al-Sharafi AM, Darem AA, Nazim K, Sattar A, Alshammeri M, Alzahrani AA, Obayya M.   +8 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

SVNC-Net: An optimized U-Net variant with 2D convolutions for lightweight 3D spleen segmentation. [PDF]

PLoS One
Genc MZ, Dalveren Y, Kara A, Derawi M, Kubicek J, Penhaker M.   +5 more
europepmc   +1 more source

Convolutional Neural Nets vs Vision Transformers: A SpaceNet Case Study with Balanced vs Imbalanced Regimes [PDF]

Akshar Gothi
openalex   +1 more source

Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems

Advanced Intelligent Discovery, EarlyView.
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley   +1 more source

A hybrid deep learning and rule-based model for smart weather forecasting and crop recommendation using satellite imagery. [PDF]

Sci Rep
Mohamed SA, Maksoud OOA, Fathy A, Mohamed AS, Hosny K, Keshk HM, Mohamed SA.   +6 more
europepmc   +1 more source