Results 61 to 70 of about 5,871 (248)

Mitigating errors in logical qubits

Communications Physics
Quantum error correcting codes can enable large quantum computations provided physical error rates are sufficiently low. We combine post-selection with surface code error correction through the use of exclusive decoders, which abort on decoding instances
Samuel C. Smith, Benjamin J. Brown, Stephen D. Bartlett   +2 more
doaj   +1 more source

Clinical validation of a real‐time machine learning‐based system for the detection of acute myeloid leukemia by flow cytometry

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Machine‐learning (ML) models in flow cytometry have the potential to reduce error rates, increase reproducibility, and boost the efficiency of clinical labs. While numerous ML models for flow cytometry data have been proposed, few studies have described the clinical deployment of such models.
Lauren M. Zuromski, Jacob Durtschi, Aimal Aziz, Jeffrey Chumley, Mark Dewey, Paul English, Muir Morrison, Keith Simmon, Blaine Whipple, Brendan O'Fallon, David P. Ng   +10 more
wiley   +1 more source

Totally defined nanocatalysis: Detection of polyelement nanoparticles by deep learning

InfoMat, EarlyView.
This work reports the combining STEM with deep learning with convolutional neural network of selected individual NPs of significant aspects of shape and size for widespread and commercially important PtPdInGaP@TiO2 NPs. The proposed method facilitates the detection and segmentation of HEA NPs, which has the potential for the development of high ...
Wail Al Zoubi, Manar Alnaasan, Bassem Assfour, Stefano Leoni, Iftikhar Hussain, Sungho Kim, Young Gun Ko   +6 more
wiley   +1 more source

From multi‐omics to precision medicine in intracranial aneurysm: Biomarker discovery and multimodal integration

Interdisciplinary Medicine, EarlyView.
This review explores intracranial aneurysm biomarker discovery through multi‐omics. It reveals key genes, proteins, and metabolites, and shows how machine‐learning‐based multi‐modal integration may aid diagnosis and treatment. Abstract Despite extensive research, currently, no biomarkers are available for clinical use in intracranial aneurysm (IA ...
Jiaxin Zhang, Yufei Yang, Bingxu Chen, Yanmeng Zhao, Haitao Sun   +4 more
wiley   +1 more source

Bounds on concatenated entanglement-assisted quantum error-correcting codes

Entanglement-assisted quantum error-correcting codes (EAQECCs) make use of pre-shared entanglement to enhance the rate of error correction and communication. We study the concatenation of EAQECCs, in specific showing how the order of concatenation affects the number of ebits consumed, the logical error probability, the pseudo-threshold, and the ...
Dash, Nihar Ranjan, Dutta, Sanjoy, Srikanth, R., Banerjee, Subhashish   +3 more
openaire   +2 more sources

Unstained Blood Smear Analysis: A Review of Rule‐Based, Machine Learning, and Deep Learning Techniques

Journal of Biophotonics, EarlyView.
Bright‐field images of unstained smears. (1) Sparse erythrocytes allow straightforward intensity‐ or phase‐based segmentation. (2) Overlapping cells blur boundaries, causing over‐ or under‐segmentation and lowering rule‐based accuracy, thus motivating overlap‐aware algorithms for reliable downstream feature extraction and classification. ABSTRACT Blood
Husnu Baris Baydargil, Thomas Bocklitz
wiley   +1 more source

CRISPR/Cas9 Knockout of Shell Matrix Protein 1 in the Slipper‐Snail Crepidula atrasolea

Journal of Experimental Zoology Part B: Molecular and Developmental Evolution, EarlyView.
Methods for CRISPR/Cas9 shell matrix protein knockout in the snail, Crepidula atrasolea including optimizing RNP delivery and embryo husbandry, to the use of Sanger and MiSeq sequencing, and high‐content screening of embryos to characterize the loss of Shell Matrix Protein 1 (SMP1) during larval shell development.
Grant Batzel, Yiqun Wang, Antonia Bock, Elbereth Chen, Stephanie Neal, Rebecca N. Lopez‐Anido, Yoon Lee, Evan Tjeerdema, Emily Ignatoff, Tejasvi Patil, Gabriela Ramirez, Maryna P. Lesoway, Amro Hamdoun, Deirdre C. Lyons   +13 more
wiley   +1 more source

Deep learning accelerated the discovery of multi‐principal element alloys with various strength‐toughness trade‐offs

Materials Genome Engineering Advances, EarlyView.
Coupling deep generative models with Pareto optimization, we uncover eight multiprincipal element alloys that outperform existing strength–toughness records after only three design–test cycles, showcasing a rapid data‐efficient route to balanced‐property alloy discovery across high‐dimensional composition spaces.
Chunhui Fan, Hong Luo, Qiancheng Zhao, Xuefei Wang, Hongxu Cheng, Yue Chang   +5 more
wiley   +1 more source

pTx‐Pulseq in hybrid sequences: Accessible and advanced hybrid open‐source MRI sequences on Philips scanners

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose To enhance the accessibility of advanced pulse sequences, or parts thereof, through the open‐source Pulseq framework. This work extends the Pulseq framework to Philips MRI systems and incorporates dynamic parallel‐transmit (pTx) capabilities within the constraints of the existing Pulseq format.
Thomas H. M. Roos, Edwin Versteeg, Mark Gosselink, Hans Hoogduin, Kyung Min Nam, Nicolas Boulant, Vincent Gras, Franck Mauconduit, Dennis W. J. Klomp, Jeroen C. W. Siero, Jannie P. Wijnen   +10 more
wiley   +1 more source