Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: QSAR modeling is a method for predicting properties, e.g. the solubility or toxicity, of chemical compounds using statistical learning techniques. QSAR is in widespread use within the pharmaceutical industry to prioritize compounds for experimental testing or to alert for potential toxicity. Hover, predictions from a QSAR model are difficult to assess if their prediction intervals are unknown.   introduce conformal prediction into the QSAR field to address this issue.  apply support vector machine regression in combination with two nonconformity measures to five datasets of different sizes to demonstrate the usefulness of conformal prediction in QSAR modeling. One of the nonconformity measures provides prediction intervals with almost the same width as the size of the QSAR models' prediction errors, showing that the prediction intervals obtained by conformal prediction are efficient and useful.
['Martin Eklund', 'Ulf Norinder', 'Scott Boyer', 'Lars Carlsson']
I am writing a research paper on a idea Application of conformal prediction in QSAR
[{"from": "human", "value": "I am writing a research paper on a idea Application of conformal prediction in QSAR"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: QSAR modeling is a method for predicting properties, e.g. the solubility or toxicity, of chemical compounds using statistical learning techniques. QSAR is in widespread use within the pharmaceutical industry to prioritize compounds for experimental testing or to alert for potential toxicity. Hover, predictions from a QSAR model are difficult to assess if their prediction intervals are unknown.   introduce conformal prediction into the QSAR field to address this issue.  apply support vector machine regression in combination with two nonconformity measures to five datasets of different sizes to demonstrate the usefulness of conformal prediction in QSAR modeling. One of the nonconformity measures provides prediction intervals with almost the same width as the size of the QSAR models' prediction errors, showing that the prediction intervals obtained by conformal prediction are efficient and useful."}]