Electronic knowledgebase (including Electronic Medical Record), together with inference procedures, form an intelligent medical information systems that offers many possibilities for health care providers. It acts as a strong base for scientific upgrading and provides an enormous support for developing new medical decisions. This paper proposes an intelligent neurosurgical decision support system framework. This framework merges the advantages of electronic medical record, rough set theory, clinical pathways, latest available scientific researches, and patient's expectations. We have designed and developed this aiming to get a support system for predicting the ideal treatment method of lumbar disc patients, in addition to evaluating the treatment plan. The system ensures future up-to-date knowledgebase, through permitting upgrading with the most recent innovations in knowledge and discoveries. This framework is expected to improve the quality of health care by providing the necessary requirements of neurosurgery domain.
Objective: Thirty patients early diagnosed within the first six months of age as primary craniosynostosis. Were operated by early suture release surgery endoscopic assisted suturectomy in neurosurgery department in Shebin Elkom Teaching hospital (2011-2016). The studied group 16 females 14 males all have primary craniosynostosis. 9 Brachycephaly, 7 scaphocephally, 4 anterior plagiocephaly, 4 trigonocephaly, 2 posterior plagiocephaly and 4 oxycephaly. 63.3% of patients presented with deformity alone. Other clinical presentations as manifestations of increased intracranial pressure (vomiting, irritable crying, and fits) and delayed milestones plus deformity was 30%, 6.7% respectively. The 3D CT volume rendering technique of all of them retrospectively studied, and Ectocranial skull suture closure grading system of Meindl and Lovejoy applied to 3D skull of the studied group as it simulate real time one. Of all patients 38 sutures was affected. After application of proposed grading 10 sutures G1, 16 sutures G2 and 12 sutures G3. Of coronal sutures 6 G1, 13G2, and 4G3. Of lambdoid sutures 2G1 and 1G3. Of metopic sutures 5 are G3. And of sagittal sutures 2G1, 3G2, and 2G3. Conclusion: Application of ectocranial skull suture closure grading system to 3D skull in early cases of primary craniosynostosis will help in precise diagnosis and surgical decision, as it demonstrate the degree of affected suture from single bony bridge that restrict or arrest suture growth in mild cases to completely obliterated one.
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