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1.
J Chem Inf Model ; 61(6): 2641-2647, 2021 06 28.
Article in English | MEDLINE | ID: covidwho-1241784

ABSTRACT

The growing quantity of public and private data sets focused on small molecules screened against biological targets or whole organisms provides a wealth of drug discovery relevant data. This is matched by the availability of machine learning algorithms such as Support Vector Machines (SVM) and Deep Neural Networks (DNN) that are computationally expensive to perform on very large data sets with thousands of molecular descriptors. Quantum computer (QC) algorithms have been proposed to offer an approach to accelerate quantum machine learning over classical computer (CC) algorithms, however with significant limitations. In the case of cheminformatics, which is widely used in drug discovery, one of the challenges to overcome is the need for compression of large numbers of molecular descriptors for use on a QC. Here, we show how to achieve compression with data sets using hundreds of molecules (SARS-CoV-2) to hundreds of thousands of molecules (whole cell screening data sets for plague and M. tuberculosis) with SVM and the data reuploading classifier (a DNN equivalent algorithm) on a QC benchmarked against CC and hybrid approaches. This study illustrates the steps needed in order to be "quantum computer ready" in order to apply quantum computing to drug discovery and to provide the foundation on which to build this field.


Subject(s)
COVID-19 , Drug Discovery , Algorithms , Computing Methodologies , Humans , Machine Learning , Quantum Theory , SARS-CoV-2 , Support Vector Machine
2.
Am J Ophthalmol ; 223: 333-337, 2021 03.
Article in English | MEDLINE | ID: covidwho-1064718

ABSTRACT

PURPOSE: To review the impact of increased digital device usage arising from lockdown measures instituted during the COVID-19 pandemic on myopia and to make recommendations for mitigating potential detrimental effects on myopia control. DESIGN: Perspective. METHODS: We reviewed studies focused on digital device usage, near work, and outdoor time in relation to myopia onset and progression. Public health policies on myopia control, recommendations on screen time, and information pertaining to the impact of COVID-19 on increased digital device use were presented. Recommendations to minimize the impact of the pandemic on myopia onset and progression in children were made. RESULTS: Increased digital screen time, near work, and limited outdoor activities were found to be associated with the onset and progression of myopia, and could potentially be aggravated during and beyond the COVID-19 pandemic outbreak period. While school closures may be short-lived, increased access to, adoption of, and dependence on digital devices could have a long-term negative impact on childhood development. Raising awareness among parents, children, and government agencies is key to mitigating myopigenic behaviors that may become entrenched during this period. CONCLUSION: While it is important to adopt critical measures to slow or halt the spread of COVID-19, close collaboration between parents, schools, and ministries is necessary to assess and mitigate the long-term collateral impact of COVID-19 on myopia control policies.


Subject(s)
COVID-19/epidemiology , Computing Methodologies , Myopia/epidemiology , Quarantine , SARS-CoV-2 , Screen Time , Adolescent , Adolescent Behavior/physiology , Child , Child Behavior/physiology , Child, Preschool , Female , Humans , Male , Myopia/physiopathology , Myopia/prevention & control , Practice Guidelines as Topic , Risk Factors , Social Media
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