Machine Learning and Data Science have enjoyed a renaissance due to the availability of increased computational power and larger data sets. Many questions can be now asked and answered, that previously were beyond our scope. This does not translate instantly into new tools that can be used by those not skilled in the field, as many of the issues and traps still exist. In this paper, we look at some of the new tools that we have created, and some of the difficulties that still need to be taken care of during the transition from a project run by an expert, to a tool for the bench chemist.
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| http://dx.doi.org/10.2533/chimia.2019.1001 | DOI Listing |
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Pivotal trial characteristics and types of endpoints used to support Food and Drug Administration rare disease drug approvals between 2013 and 2022.
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Rare Diseases Team, Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Background/aims: Rare disease drug development faces unique challenges, such as genotypic and phenotypic heterogeneity within small patient populations and a lack of established outcome measures for conditions without previously successful drug development programs. These challenges complicate the process of selecting the appropriate trial endpoints and conducting clinical trials in rare diseases. In this descriptive study, we examined novel drug approvals for non-oncologic rare diseases by the U.
View Article and Find Full Text PDFIn the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
View Article and Find Full Text PDFSUMO-Specific Peptidase 5 Promotes Oesophageal Squamous Cell Carcinoma Growth through the NF-κB- Axis.
Front Biosci (Landmark Ed)
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Department of Cardiothoracic Surgery, The Affiliated Jiangyin Hospital of Nantong University, 214400 Jiangyin, Jiangsu, China.
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Hydroxyapatite Chitosan Gradient Pore Scaffold Activates Oxidative Phosphorylation Pathway to Induce Bone Formation.
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Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Fujian Medical University, Fujian Provincial Key Laboratory of Stomatology, National Regional Medical Center, Binhai Campus of The First Affiliated Hospital, 350005 Fuzhou, Fujian, China.
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Analysis of "Dose Accuracy and Reliability of a Connected Insulin Pen System".
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Division of Endocrinology, Diabetes & Metabolism, Weill Cornell Medicine, New York, NY, USA.
In an article in the , Backfish and coauthors examined the dose accuracy and reliability of the Tempo Pen and Tempo Smart Button connected insulin pen system. This study sponsored by Eli Lilly and Company found that this system met the International Organization for Standardization 11608-1:2014 requirements for dose accuracy at a range of doses, as well as the data transfer requirements after all injections. While these results are very encouraging, they were based on simulated human factors data while data from a human factors validation study where individuals successfully dialed and administered correct doses was not reported.
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