A system for training a mathematical model for detecting a medical condition and for detecting the medical condition using the mathematical model, wherein the medical condition is a concussion or Alzheimer's disease, the system comprising at least one computer configured to: obtain a training corpus comprising speech data items, wherein each speech data item is labelled with a diagnosis value, and wherein each speech data item corresponds to a prompt; obtain speech recognition results for each speech data item using automatic speech recognition, wherein the speech recognition results for a speech data item comprise a transcription of the speech data item; compute a plurality of acoustic features for each speech data item in the training corpus, wherein the plurality of acoustic features is computed from the speech data item and wherein computation of the plurality of acoustic features does not use the speech recognition results of the speech data item; compute a plurality of language features for each speech data item in the training corpus by processing the speech recognition results; compute a feature selection score for each feature of the plurality of acoustic features and each feature of the plurality of language features, wherein: the feature selection score for a feature indicates a usefulness of the feature for detecting the medical condition, and the feature selection score is computed using, for each speech data item, a value of the feature and the diagnosis value corresponding to the speech data item; select a plurality of features from the plurality of acoustic features and the plurality of language features using the feature selection scores; train the mathematical model for detecting the medical condition using the selected plurality of features for each speech data item of the training corpus; deploy a product or service for detecting the medical condition using the mathematical model; present, by the product or service, a prompt to a person; receive a speech data item corresponding to speech of the person in response to the prompt; and compute a medical diagnosis score by processing the speech data item using the mathematical model, the medical diagnosis score comprising a determination of whether the person may have the medical condition or a possible severity of the medical condition. obtain a training corpus comprising speech data items, wherein each speech data item is labelled with a diagnosis value, and wherein each speech data item corresponds to a prompt; obtain speech recognition results for each speech data item using automatic speech recognition, wherein the speech recognition results for a speech data item comprise a transcription of the speech data item; compute a plurality of acoustic features for each speech data item in the training corpus, wherein the plurality of acoustic features is computed from the speech data item and wherein computation of the plurality of acoustic features does not use the speech recognition results of the speech data item; compute a plurality of language features for each speech data item in the training corpus by processing the speech recognition results; compute a feature selection score for each feature of the plurality of acoustic features and each feature of the plurality of language features, wherein: the feature selection score for a feature indicates a usefulness of the feature for detecting the medical condition, and the feature selection score is computed using, for each speech data item, a value of the feature and the diagnosis value corresponding to the speech data item; the feature selection score for a feature indicates a usefulness of the feature for detecting the medical condition, and the feature selection score is computed using, for each speech data item, a value of the feature and the diagnosis value corresponding to the speech data item; select a plurality of features from the plurality of acoustic features and the plurality of language features using the feature selection scores; train the mathematical model for detecting the medical condition using the selected plurality of features for each speech data item of the training corpus; deploy a product or service for detecting the medical condition using the mathematical model; present, by the product or service, a prompt to a person; receive a speech data item corresponding to speech of the person in response to the prompt; and compute a medical diagnosis score by processing the speech data item using the mathematical model, the medical diagnosis score comprising a determination of whether the person may have the medical condition or a possible severity of the medical condition.