Detalhe da pesquisa
1.
Emin: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability.
J Chem Inf Model
; 64(4): 1277-1289, 2024 Feb 26.
Artigo
em Inglês
| MEDLINE | ID: mdl-38359461
2.
Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning.
J Phys Chem A
; 127(28): 5914-5920, 2023 Jul 20.
Artigo
em Inglês
| MEDLINE | ID: mdl-37406209
3.
Peripheral Oxygen Saturation Facilitates Assessment of Respiratory Dysfunction in the Sequential Organ Failure Assessment Score With Implications for the Sepsis-3 Criteria.
Crit Care Med
; 50(3): e272-e283, 2022 03 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-34406170
4.
Improving the Accuracy of Composite Methods: A G4MP2 Method with G4-like Accuracy and Implications for Machine Learning.
J Phys Chem A
; 126(27): 4528-4536, 2022 Jul 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-35786965
5.
A comparison of predictors for mortality and bacteraemia in patients suspected of infection.
BMC Infect Dis
; 21(1): 864, 2021 Aug 23.
Artigo
em Inglês
| MEDLINE | ID: mdl-34425790
6.
Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models.
J Phys Chem A
; 125(27): 5990-5998, 2021 Jul 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-34191512
7.
Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.
J Chem Phys
; 155(20): 204801, 2021 Nov 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-34852489
8.
Quantum-Chemically Informed Machine Learning: Prediction of Energies of Organic Molecules with 10 to 14 Non-hydrogen Atoms.
J Phys Chem A
; 124(28): 5804-5811, 2020 Jul 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-32539388
9.
Clinical- vs. model-based selection of patients suspected of sepsis for direct-from-blood rapid diagnostics in the emergency department: a retrospective study.
Eur J Clin Microbiol Infect Dis
; 38(8): 1515-1522, 2019 Aug.
Artigo
em Inglês
| MEDLINE | ID: mdl-31079313
10.
Computer Vision-aided in situ TEM Studies of Microstructure Evolution under Irradiation.
Microsc Microanal
; 29(Supplement_1): 1495, 2023 Jul 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-37613834
11.
Prehospital Early Warning Scores to Predict Mortality in Patients Using Ambulances.
JAMA Netw Open
; 6(8): e2328128, 2023 08 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-37556138
12.
Machine-Learning Model for Mortality Prediction in Patients With Community-Acquired Pneumonia: Development and Validation Study.
Chest
; 163(1): 77-88, 2023 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-35850287
13.
Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data.
Sci Rep
; 13(1): 11760, 2023 07 20.
Artigo
em Inglês
| MEDLINE | ID: mdl-37474597
14.
14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon.
Digit Discov
; 2(5): 1233-1250, 2023 Oct 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-38013906
15.
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.
bioRxiv
; 2022 Nov 23.
Artigo
em Inglês
| MEDLINE | ID: mdl-36451881
16.
Models and Processes to Extract Drug-like Molecules From Natural Language Text.
Front Mol Biosci
; 8: 636077, 2021.
Artigo
em Inglês
| MEDLINE | ID: mdl-34527701
17.
Enabling deeper learning on big data for materials informatics applications.
Sci Rep
; 11(1): 4244, 2021 02 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-33608599
18.
Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl.
J Phys Chem Lett
; 12(17): 4278-4285, 2021 May 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-33908789
19.
Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population: observational study using electronic health records data.
BMJ Qual Saf
; 29(9): 735-745, 2020 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-32029574
20.
A High-Throughput Structural and Electrochemical Study of Metallic Glass Formation in Ni-Ti-Al.
ACS Comb Sci
; 22(7): 330-338, 2020 07 13.
Artigo
em Inglês
| MEDLINE | ID: mdl-32496755