Artificial Intelligence in Medicine
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Fundamentals of clinical methodology: 2. Etiology.
The concept of etiology is analyzed and the possibilities and limitations of deterministic, probabilistic, and fuzzy etiology are explored. Different kinds of formal structures for the relation of causation are introduced which enable us to explicate the notion of cause on qualitative, comparative,...
Distributed cognition and knowledge-based controlled medical terminologies.
Controlled medical terminologies (CMTs) are playing central roles in clinical information systems and medical knowledge resource applications. As these terminologies grow, they are able to support more complex tasks but require more intensive efforts to create and maintain them. Several terminologie...
Dependency parsing for medical language and concept representation.
We present a PROLOG-based formalization of dependency grammar that can accommodate conceptual structures in its dependency rules. First results indicate that this formalization provides an operational basis for the implementation of medical language parsers and for the design of medical concept repr...
Cue-based assertion classification for Swedish clinical text--developing a lexicon for pyConTextSwe.
We continue our study of porting an assertion system (pyConTextNLP) from English to Swedish (pyConTextSwe) by creating an optimized assertion lexicon for clinical Swedish. We integrated cues from four external lexicons, along with generated inflections and combinations. We used subsets of a clinical...
Transferring brain-computer interfaces beyond the laboratory: successful application control for motor-disabled users.
We report our experiences of training 24 motor-disabled participants at rehabilitation clinics or at the end-users' homes, without BCI experts present. We also share the lessons that we have learned through transferring BCI technologies from the lab to the user's home or clinics. The most important...
Evaluation of a clinical decision support algorithm for patient-specific childhood immunization.
We compared vaccine recommendations from the CDSS for both eligible and recommended timelines, based on the child's date of birth and vaccine history, to recommendations from registered nurses who routinely selected vaccines for administration in a busy inner city hospital, using the same date of bi...
Improved modeling of clinical data with kernel methods
Objective Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate...
Multiple kernel learning in protein-protein interaction extraction from biomedical literature.
We present a weighted multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, graph and part-of-speech (POS) path. In particular, we extend the shortest path-enclosed tree (SPT) and dependency...
Conversational case-based reasoning in medical decision making
We present an approach to CCBR in medical classification and diagnosis that aims to increase transparency while also providing high levels of accuracy and efficiency....
Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study
Objective We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification.