Speech analysis can be used for healthcare tasks such as pathology detection. Conventionally, a speech-language pathologist is specialized to detect anomalies from speech. Speech disorders result from a variety of causes such as brain injury, stroke, hearing loss, developmental delay or emotion alteration. Content of the speech is often not of interest for pathology detection, but characteristics are. In the literature of automatic pathology detection by speech analysis, physiological pathologies such as nodule and cancer are taken into account along with neurodegenerative brain disorders such as Parkinson's disease, Alzheimer's disease and mild cognitive impairment. As the problem of pathology detection from speech has become a vast research area, comprehensive reviews are needed by researchers to contribute novel approaches. In this study, a literature survey on pathology detection is provided including data types, features, classification methods and accuracy rates