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Detect Adverse Events and Medication Errors Using Technology
Get PDFTechnology has changed the practice of pharmacy. Many systems are now part of an ever increasingly interfaced or integrated health care system allowing the electronic exchange of prescriptions from electronic health records (EHRs) to the pharmacy information system and bidirectional data exchange for many items, such as lab results and test information. With meaningful use of automated distribution cabinet databases, EHR efforts, electronic data exchange, and smart pump technology, the availability of data to use for addressing and preventing adverse medication events has grown. Use of these systems has allowed a data-rich environment to store and retrieve reporting. Mining data is becoming easier and can be used as a tool to identify adverse medication events or potential events
The Current State of the Field: Australasian Stories
No full textThis session featured two presentations on 20th-century preaching in the Australasian region
The U-Net-based Active Learning Framework for Enhancing Cancer Immunotherapy
Get PDFBreast cancer is the most common cancer in the world. According to the U.S. Breast Cancer Statistics, about 281,000 new cases of invasive breast cancer are expected to be diagnosed in 2021 (Smith et al., 2019). The death rate of breast cancer is higher than any other cancer type. Early detection and treatment of breast cancer have been challenging over the last few decades. Meanwhile, deep learning algorithms using Convolutional Neural Networks to segment images have achieved considerable success in recent years. These algorithms have continued to assist in exploring the quantitative measurement of cancer cells in the tumor microenvironment. However, detecting cancerous regions in whole-slide images has been challenging as it requires substantial annotation and training efforts from clinicians and biologists. In this thesis, a notable instructing process named U-Net-based Active Learning is proposed to improve the annotation and training procedure in a feedback learning process by utilizing a Deep Convolutional Neural Networks model. The proposed approach reduces the amount of time and effort required to analyze the whole slide images. During the Active Learning process, highly uncertain samples are iteratively selected to strategically supply characteristics of the whole slide images to the training process using a low-confidence sample selection algorithm. The performance results of the proposed approach indicated that the U-Net-based Active Learning framework has promising outcomes in the feedback learning process as it reaches 88.71% AUC-ROC when only using 64 image patches, while random lymphocyte prediction reaches 84.12% AUC-ROC at maximum
Utility and yield of genetic testing leading to a definitive neuromuscular or neuropathic diagnosis at a rural outpatient neurology clinic affiliated with a university health center in West Virginia over 4 years.
Get PDFIntroduction
Clinicians are increasingly relying on genetic testing to pinpoint definite diagnoses. A more general diagnosis of neuropathy or neuromuscular disease like myopathy can be narrowed down substantially using genetic testing. Because carrier status is of utmost importance in reproductive matters, pathogenic results can prognosticate the future course of the illness and help plan ahead for treatment and social supports. Given the expense of genetic testing, it is important to assess the cost-benefit ratio to determine whether it is worthwhile to collect genetic samples. The purpose of the study was to determine the likelihood of obtaining a conclusive confirmatory diagnosis through genetic testing (measured as the percent of positive results obtained out of all the submitted samples).
Methods
A single clinician’s record of genetic test outcomes was reviewed spanning four years from July 2015 to June 2019 to identify those who had submitted genetic samples to Invitae, a commercial lab in California that offers affordable genetic testing. All patients were evaluated for complaints of neuromuscular and neuropathic nature using the standard of care workup that included a physical exam, lab tests, nerve conduction study (NCS), electromyography (EMG), and/or muscle biopsy before sending out for genetic testing. The positive, negative, and indeterminate genetic diagnoses were tabulated, and the individual disease entities’ prevalence was determined.
Results
Of the patients who participated in genetic testing, 96 were diagnosed with neuropathic conditions and 59 with neuromuscular conditions. The patients’ health records did not have to be mined for results because the clinician’s Invitae account contained de-identified requisition numbers linked to their results. The patients in the neuromuscular group had twice as many positive results as those in the neuropathic group. There were about three times as many normal results in the neuropathic group compared to the neuromuscular group. Around half of all test samples showed indeterminate results containing variants of unknown significance (VOUS), which were not indicative of any pathology and were considered inconclusive.
Conclusion
Based on the study findings, there were 17.7% and 35.6% positive (meaning pathogenic) results, respectively, among neuropathic and neuromuscular cases sent off for genetic analysis. While 38 out of 155 total cases makes up a small, 24.5% yield of abnormal results, genetic studies are still a worthwhile addition to investigating neuropathic and neuromuscular cases
Yeager Family Genealogy
Get PDFDetailed overview of Yeager Family genealogy from 1800-1928 provided by Frank Yeager. First Yeager came to America from Ireland to Jackson County, Ohio, and another came to Lincoln County, West Virginia.https://mds.marshall.edu/yeager/1003/thumbnail.jp
The first troglobitic scorpions from Hispaniola, Greater Antilles: two new species of \u3cem\u3eCazierius\u3c/em\u3e Francke, 1978 (Scorpiones: Diplocentridae)
Get PDFTwo new species of the Greater Antillean endemic scorpion genus Cazierius Francke, 1978, are herein described from the island of Hispaniola. They were found inside isolate limestone caves in the Dominican Republic and are fully troglomorphic, thus, apparently being strict troglobites that represent the first ever documented for this genus. The present additions raise the number of Hispaniolan species of both Cazierius and the family Diplocentridae Karsch, 1880, to five and ten, respectively
