Spotlight

A paper on LogReg is available (both paper and presentation are avaiable in Slovene as well).

A PowerPoint presentation on decisions at hand concept is available.


FRI > Biolab > Decisions at Hand

Decision at Hand

Professional decision making often takes place just about anywhere: at the office, walking through the park, talking with the customer, while drinking coffee, etc. To support and raise the quality of decisions, computerized decision support tools are being constructed for various purposes. Their major advantage is their speed, support of systematic approach to decision making, ability to explain decisions, and objectively - according to decision mode - rank (possibly a large set of) variants.

Their biggest disadvantage, though, is the computer, which often is not available where the decisions are made. In medicine, for instance, a physician can not take a break with his patient to jump into his office, switch on the computer, run the software, type in the data, and then run back to the patient (which is right then probably knocking at the office of a colleague-physician).

We are building a set of decision support shells that should work both on handheld computers and on web to alleviate these problems. We call our schema decisions-at-hand. In this schema, machine learning (data mining) and/or statistical analysis is used to develop decision models from data; these are then encoded in XML, and used in decision shells either on web or on a handheld device.

When fully developed, the decisions-at-hand will consists of:

  • A definition of structure for an XML document that encodes the model;
  • Palm-based decision support software which can handle XML documents mentioned above;
  • Web-based decision support shell. The software currently supports logistic regression and naive bayesian decision support models, other models may be encoded through feature transformations.
  • PocketPC-based decision support shell (coming in March 2003). Early implementations were based on PalmOS.
  • Wizards that, given the data set, construct predictive models and encode them in XML. For this, we will use Orange and Orange Widgets platforms. A web-wizard for construction of naive Bayesian model will be availbe in May 2003.

Decisions-at-hand schema is being tested on several applications, including:

  • Prostate Cancer Prognostics (with Mike Kattan from Memorial Sloan-Kettering Cancer Center, New York, NY)
  • Prognostics in Trauma and Emergency Medicine (with Noriaki Aoki and J. Robert Beck, Baylor College of Medicine, Houston, TX)
  • Prognostics and Therapy evaluation after severe hip and hand injuries (with Dragica Smrke, Clinical Center, Ljubljana, Slovenia)