You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

The COVID-19 pandemic resulted in a significant increase in the workload for the emergency systems and healthcare providers all around the world. The emergency systems are dealing with large number of patients in various stages of deteriorating conditions which require significant medical expertise for accurate and rapid diagnosis and treatment. This issue will become more prominent in places with lack of medical experts and state-of-the-art clinical equipment, especially in developing countries. The machine intelligence aided medical diagnosis systems can provide rapid, dependable, autonomous, and low-cost solutions for medical diagnosis in emergency conditions. In this paper, a privacy-preserving computer-aided diagnosis (CAD) framework, called Decentralized deep Emergency response Intelligence (D-EI), which provides secure machine learning based medical diagnosis on the cloud is proposed. The proposed framework provides a blockchain based decentralized machine learning solution to aid the health providers with medical diagnosis in emergency conditions. The D-EI uses blockchain smart contracts to train the CAD machine learning models using all the data on the medical cloud while preserving the privacy of patients' records. Using the proposed framework, the data of each patient helps to increase the overall accuracy of the CAD model by balancing the diagnosis datasets with minority classes and special cases. As a case study, the D-EI is demonstrated as a solution for COVID-19 diagnosis. The D-EI framework can help in pandemic management by providing rapid and accurate diagnosis in overwhelming medical workload conditions.
["Diagnosis"]