Tuesday 5th June

Another TMA day. The word count is very restrictive. I've tried but I can't get it near the 800 words per question. Almost done. Will submit tomorrow.

Monday 4th June

Answered question 1 a of TMA o2. Realised in answering 1 b that my literature search was rather crap but I'll answer as best I can and continue to search for more information as the project progresses. For all the searching I have done on IEEE Xplore etc the papers I have found are rather high powered and quickly lose me when they delve into mathematical formulae. I have found general sites like Wikipedia far more interesting and useful.

Sunday Evening

Ran a very rudimentary flex program with one rule but at least it worked and it's a start. I loathe using flex but I've got to get to grips with it. I've started from the boiler example in T396 and it works so I'll just work through the examples I've got gradually till I get to an object based program using certainty factors. I may yet try another way of handling uncertainty in the data.

Now back to the TMA.

Sunday 3rd June

Have modified an old flex progam from T396 to test the 3 rules that are correct all the time just to ensure this works OK (rbs1.ksl). The presentation of the questions will have to change and I will need to add the further rules with certainty factors for true comparison with the neural networks.

Started TMA write up yesterday. Should be OK.

Saved the training file as an MS-DOS text file from excel and this trains the MLP without error. However the test data saved in the same format does run but the output file does not contain data that can be interpreted. I will have to spend some time looking at this.

Wednesday 30th May

I went through the PROMPT criteria for evaluating information from the literature search in preparation for the TMA. Have booked 2 days off to get it done. Have been trawling around for information in journal articles to include in the project. The MIT course lecture notes for Medical Artificial Intelligence are heavy going but there is some relevant information about neural networks.

Tuesday 29th May

Have now finished preprocessing the data for the neural network and created a training file of 50 random patients. Have also created the test file of all 285 cases for the neural network. I created a multi-layered perceptron with 32 input neurons, 10 hidden layer neurons and 2 output neurons and tried to train this simple network. However neural works errors with the training file. This is a text file with a .nnb file extension. I will make sure that this file is the correct format for neural work and recheck the number of neurons.

Sunday 27th May

Have been spending a lot of time preprocessing the breast cancer data for the neural network. Until this is complete I cannot start testing. I have taken my tutors advice and tried to reduce the number of input neurons, though I have still probably got too many. The statistical analysis of the data suggested that some attributes have no influence on tumour recurrance. The location of the tumour in the breast which I took a long time converting into quadrants (and the centre) seems to have no influence on recurrance, because there is a roughly 70% / 30% split between non-recurrence and recurrance which is the same as looking at the overall ratio of non-recurrence to recurrence. Also some attributes are related. For example the menopausal status is age related so I have removed menopausal status.

I will now carry on with this preprocessing which is rather laborious because I am doing it manually. I do not have the expertise to covert the raw data into the format required by the neural network any other way. There are likely to be mistakes in this conversion but I am trying to be as meticulous as I can.