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Asset logo for symbol LUNG
Asset logo for symbol LUNG



AI Deep-Learning Forecast (LUNG)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Pulmonx (LUNG) Stocklytics Forecast

Pulmonx Corp, also known as LUNG, is a medical device company that focuses on developing minimally invasive solutions to improve the lives of patients with severe lung diseases. The company specializes in the treatment of Chronic Obstructive Pulmonary Disease (COPD) and severe emphysema, which are major causes of morbidity and mortality worldwide. With a mission to transform the lives of patients suffering from debilitating lung diseases, Pulmonx Corp has garnered significant attention and interest from investors and analysts alike.
When it comes to predicting the future stock price of Pulmonx Corp (LUNG), it is important to consider various factors that can impact the company's performance. While no prediction can be completely accurate, analysts and experts often rely on fundamental analysis, market trends, and historical data to forecast the potential trajectory of the stock. However, it is important to note that stock prices are influenced by numerous variables, including market conditions, industry dynamics, and company-specific factors.
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Frequently Asked Questions

What is the analyst price prediction for Pulmonx (LUNG) stock?
Analysts have set a target price of $14.6 for Pulmonx (LUNG), based on forecasts from 29 analysts. The predicted price range extends from a high of $25 to a low of $6. This represents a potential increase of up to 200.84% and a decrease of -27.8% from the current price of $8.31. These forecasts are as of 2022 Aug 03.
What are the analyst ratings for Pulmonx (LUNG) stock?
Currently, there are no analyst ratings available for Pulmonx (LUNG), possibly due to insufficient coverage or recent updates.
What is the AI price prediction for Pulmonx (LUNG) stock?
At present, there is no AI or machine-learning-based price prediction available for Pulmonx (LUNG) stock. The lack of a forecast could stem from various factors, such as inadequate data or the necessity for model recalibration.

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