Computer assisted methods for diagnosing diseases

In a networked computer environment comprising a communication station in communication with a computation station, said computation station comprising a trained neural network, a method for prognosing a disease, diagnosing a disease, determining a severity of a disease, screen for a disease, or a determine a likelihood of obtaining a disease in a patient, comprising the computer implemented steps of:

• at said communication station, receiving patient data and storing said patient data in a patient data file;
• at said computation station, receiving said patient data file from said communication station and introducing said patient data file into a trained neural network, wherein said trained neural network is trained with a method comprising:
• preprocessing patient biomarkers, comprising:
• selecting patient biomarkers associated with the disease process;
• statistically and/or computationally testing discriminating power of the selected patient biomarkers individually in linear and/or non-linear combination for indicating the presence or the absence or the severity of the disease, or the likelihood of obtaining the disease;
• applying statistical, mathematical, or computational tools, and/or expert knowledge for the derivation of secondary inputs to the neural network that are linear or non-linear combinations of the original or transformed biomarkers;
• selecting only those patient biomarkers or derived secondary inputs that show discriminating power;
• and
• training the computer-based neural network using the preprocessed patient biomarkers or derived secondary inputs;
• and
• at said computation station, in response to said trained neural network processing said patient data file, receiving an output value from said trained neural network, said output value corresponding to the presence of the disease, the absence of the disease, the severity of the disease, or the likelihood of obtaining the disease.