{"id":{"repo_id":"greece","oai_identifier":"oai:10442/1591"},"canonical_url":"https://search.dev.ndltd.org/etd/greece/oai:10442/1591","repository":{"repo_id":"greece","name":"Greek National Archive of PhD Theses","base_url":"https://phdtheses.ekt.gr/eadd_oai/request"},"display":{"title":"Η λήψη αντικειμενικών αποφάσεων στην τεχνητή διατροφή με την βοήθεια ηλεκτρονικού υπολογιστή (Computer assisted medical decision making)","abstract":"Malnutrition is common in surgical patients and may be an important determinant of operative morbidity and mortality. As in all branches of medicine the history is still the more important of diagnosis, so in nutritional assessment the clinical examination is used to identify patients likely to develop nutritionally associated complications (NAC). However to make explicit the implicit information found in clinical history it is necessary the development of the field of applying mathematics to clinical medicine. This thesis, stimulated by the recent advances in probability and decision theory, reintroduces a different form of Bayes's theorem that allows calculation of the patient's probability to develop NACs by adding quantities known as \"weights\". A weight combines information found in both a symptom's or sign's sensitivity and specificity. Although these statistical calculation cannot replace clinical experience and judgement, calculated probabilities based on weights can provide reasonable estimates and offer valuable lessons in clinical nutritional assessment. This methodology allows to the clinician to involve combinations of clinical symptoms or signs and test results and to choose the optimum course of action for the patient. We conclude that the use of weights and this form of Bayes' theorem should allow clinicians to evaluate clinical nutritional assessment more easily, by quantifying the likelihood of occurrence of a symptom or sign, and use probability theory in their practice. We suggest in the future, both sensitivities and specificities and weights be calculated when new symptoms and tests are evaluated.","abstract_html":"Malnutrition is common in surgical patients and may be an important determinant of operative morbidity and mortality. As in all branches of medicine the history is still the more important of diagnosis, so in nutritional assessment the clinical examination is used to identify patients likely to develop nutritionally associated complications (NAC). However to make explicit the implicit information found in clinical history it is necessary the development of the field of applying mathematics to clinical medicine. This thesis, stimulated by the recent advances in probability and decision theory, reintroduces a different form of Bayes's theorem that allows calculation of the patient's probability to develop NACs by adding quantities known as "weights". A weight combines information found in both a symptom's or sign's sensitivity and specificity. Although these statistical calculation cannot replace clinical experience and judgement, calculated probabilities based on weights can provide reasonable estimates and offer valuable lessons in clinical nutritional assessment. This methodology allows to the clinician to involve combinations of clinical symptoms or signs and test results and to choose the optimum course of action for the patient. We conclude that the use of weights and this form of Bayes' theorem should allow clinicians to evaluate clinical nutritional assessment more easily, by quantifying the likelihood of occurrence of a symptom or sign, and use probability theory in their practice. We suggest in the future, both sensitivities and specificities and weights be calculated when new symptoms and tests are evaluated.","abstract_has_math":false,"creators":["Markou, Spyridon","Μάρκου, Σπυρίδων"],"institution":"University of Patras","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1991,"date_issued":"1991","date_published":"1991","updated_at":"2026-07-24T02:25:02Z","subjects":["Εκτίμηση της θρέψης","Ηλεκτρονικός υπολογιστής","Θεώρημα Bayes","Θεωρία Πιθανοτήτων","Ιατρική πληροφορική","Στήριξη αποφάσεων","Τεχνητή διατροφή","Bayes' theorem","Computers","Decision analysis","Medical informatics","Nutrition","Nutritional assessment","Probability Theory","Weight of evidence of asymptoms","Φυσικές Επιστήμες","Επιστήμη Ηλεκτρονικών Υπολογιστών και Πληροφορική","Ιατρική και Επιστήμες Υγείας","Άλλες Ιατρικές Επιστήμες","Natural Sciences","Computer and Information Sciences","Medical and Health Sciences","Other Medical Sciences"],"languages":["gre"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10.12681/eadd/1591"],"render_values":[{"text":"10.12681/eadd/1591","href":"https://doi.org/10.12681/eadd/1591","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10442/hedi/1591","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Markou, Spyridon","Μάρκου, Σπυρίδων"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["1991"]},{"key":"dc:publisher","label":"Institution","values":["University of Patras","Πανεπιστήμιο Πατρών"]},{"key":"dc:type","label":"Dc Type","values":["PhD Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Εκτίμηση της θρέψης","Ηλεκτρονικός υπολογιστής","Θεώρημα Bayes","Θεωρία Πιθανοτήτων","Ιατρική πληροφορική","Στήριξη αποφάσεων","Τεχνητή διατροφή","Bayes' theorem","Computers","Decision analysis","Medical informatics","Nutrition","Nutritional assessment","Probability Theory","Weight of evidence of asymptoms","Φυσικές Επιστήμες","Επιστήμη Ηλεκτρονικών Υπολογιστών και Πληροφορική","Ιατρική και Επιστήμες Υγείας","Άλλες Ιατρικές Επιστήμες","Natural Sciences","Computer and Information Sciences","Medical and Health Sciences","Other Medical Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["gre"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10.12681/eadd/1591","http://hdl.handle.net/10442/hedi/1591"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Malnutrition is common in surgical patients and may be an important determinant of operative morbidity and mortality. As in all branches of medicine the history is still the more important of diagnosis, so in nutritional assessment the clinical examination is used to identify patients likely to develop nutritionally associated complications (NAC). However to make explicit the implicit information found in clinical history it is necessary the development of the field of applying mathematics to clinical medicine. This thesis, stimulated by the recent advances in probability and decision theory, reintroduces a different form of Bayes's theorem that allows calculation of the patient's probability to develop NACs by adding quantities known as \"weights\". A weight combines information found in both a symptom's or sign's sensitivity and specificity. Although these statistical calculation cannot replace clinical experience and judgement, calculated probabilities based on weights can provide reasonable estimates and offer valuable lessons in clinical nutritional assessment. This methodology allows to the clinician to involve combinations of clinical symptoms or signs and test results and to choose the optimum course of action for the patient. We conclude that the use of weights and this form of Bayes' theorem should allow clinicians to evaluate clinical nutritional assessment more easily, by quantifying the likelihood of occurrence of a symptom or sign, and use probability theory in their practice. We suggest in the future, both sensitivities and specificities and weights be calculated when new symptoms and tests are evaluated.","Η κακή θρέψη είναι συχνή σε χειρουργικούς ασθενείς και αποτελεί έναν σημαντικό παράγοντα κινδύνου εγχειρητικής νοσηρότητας και θνητότητας. Όπως σε όλους τους κλάδους της κλινικής ιατρικής το ιστορικό είναι το σημαντικότερο στοιχείο για να τεθεί η διάγνωση, έτσι και στην εκτίμηση της θρέψης η κλινική εξέταση χρησιμοποιείται στην αναγνώριση των ασθενών που θ’ αναπτύξουν τις λεγόμενες Σχετικές με την Κακή Θρέψη Επιπλοκές. Για να μπορέσει όμως η κλινική εξέταση να μετατραπεί από διαγνωστικό σε προγνωστικό εργαλείο είναι απαραίτητο να υποστεί την κατάλληλη επεξεργασία από τον κλάδο των εφαρμοσμένων μαθηματικών. Η διατριβή αυτή, έχοντας ως κίνητρο τα πρόσφατα επιτεύγματα της Θεωρίας των Πιθανοτήτων και της Στήριξης Αποφάσεων, χρησιμοποιεί μία διαφορετική μορφή του πολύ γνωστού θεωρήματος του Bayes, το οποίο επιτρέπει τον υπολογισμό της πιθανότητας συγκεκριμένου ασθενή ν' αναπτύξει μία η περισσότερες επιπλοκές. Η μορφή αυτή του θεωρήματος χρησιμοποιεί το λεγόμενο Βάρος Μαρτυρίας ενός συμπτώματος, που περιέχει πληροφορίες για την ευαισθησία και ειδικότητα του συμπτώματος. Προσθέτοντας τα Βάρη Μαρτυρίας των συμπτωμάτων του ασθενή μπορούμε να επιτύχουμε ικανοποιητική πρόγνωση των επιπλοκών. Αυτή η μεθοδολογία, αν και δεν προτίθεται ν’ αντικαταστήσει την εμπειρία και κρίση του γιατρού, εν τούτοις προσφέρει μία σημαντική βοήθεια στην εκτίμηση της θρέψης."]},{"key":"dc:title","label":"Title","values":["Η λήψη αντικειμενικών αποφάσεων στην τεχνητή διατροφή με την βοήθεια ηλεκτρονικού υπολογιστή (Computer assisted medical decision making)","Computer assisted medical decision making in nutritional assessment"]}]}],"canonical_facts":{"dc:creator":["Markou, Spyridon","Μάρκου, Σπυρίδων"],"dc:date":["1991"],"dc:description":["Malnutrition is common in surgical patients and may be an important determinant of operative morbidity and mortality. As in all branches of medicine the history is still the more important of diagnosis, so in nutritional assessment the clinical examination is used to identify patients likely to develop nutritionally associated complications (NAC). However to make explicit the implicit information found in clinical history it is necessary the development of the field of applying mathematics to clinical medicine. This thesis, stimulated by the recent advances in probability and decision theory, reintroduces a different form of Bayes's theorem that allows calculation of the patient's probability to develop NACs by adding quantities known as \"weights\". A weight combines information found in both a symptom's or sign's sensitivity and specificity. Although these statistical calculation cannot replace clinical experience and judgement, calculated probabilities based on weights can provide reasonable estimates and offer valuable lessons in clinical nutritional assessment. This methodology allows to the clinician to involve combinations of clinical symptoms or signs and test results and to choose the optimum course of action for the patient. We conclude that the use of weights and this form of Bayes' theorem should allow clinicians to evaluate clinical nutritional assessment more easily, by quantifying the likelihood of occurrence of a symptom or sign, and use probability theory in their practice. We suggest in the future, both sensitivities and specificities and weights be calculated when new symptoms and tests are evaluated.","Η κακή θρέψη είναι συχνή σε χειρουργικούς ασθενείς και αποτελεί έναν σημαντικό παράγοντα κινδύνου εγχειρητικής νοσηρότητας και θνητότητας. Όπως σε όλους τους κλάδους της κλινικής ιατρικής το ιστορικό είναι το σημαντικότερο στοιχείο για να τεθεί η διάγνωση, έτσι και στην εκτίμηση της θρέψης η κλινική εξέταση χρησιμοποιείται στην αναγνώριση των ασθενών που θ’ αναπτύξουν τις λεγόμενες Σχετικές με την Κακή Θρέψη Επιπλοκές. Για να μπορέσει όμως η κλινική εξέταση να μετατραπεί από διαγνωστικό σε προγνωστικό εργαλείο είναι απαραίτητο να υποστεί την κατάλληλη επεξεργασία από τον κλάδο των εφαρμοσμένων μαθηματικών. Η διατριβή αυτή, έχοντας ως κίνητρο τα πρόσφατα επιτεύγματα της Θεωρίας των Πιθανοτήτων και της Στήριξης Αποφάσεων, χρησιμοποιεί μία διαφορετική μορφή του πολύ γνωστού θεωρήματος του Bayes, το οποίο επιτρέπει τον υπολογισμό της πιθανότητας συγκεκριμένου ασθενή ν' αναπτύξει μία η περισσότερες επιπλοκές. Η μορφή αυτή του θεωρήματος χρησιμοποιεί το λεγόμενο Βάρος Μαρτυρίας ενός συμπτώματος, που περιέχει πληροφορίες για την ευαισθησία και ειδικότητα του συμπτώματος. Προσθέτοντας τα Βάρη Μαρτυρίας των συμπτωμάτων του ασθενή μπορούμε να επιτύχουμε ικανοποιητική πρόγνωση των επιπλοκών. Αυτή η μεθοδολογία, αν και δεν προτίθεται ν’ αντικαταστήσει την εμπειρία και κρίση του γιατρού, εν τούτοις προσφέρει μία σημαντική βοήθεια στην εκτίμηση της θρέψης."],"dc:identifier":["10.12681/eadd/1591","http://hdl.handle.net/10442/hedi/1591"],"dc:language":["gre"],"dc:publisher":["University of Patras","Πανεπιστήμιο Πατρών"],"dc:subject":["Εκτίμηση της θρέψης","Ηλεκτρονικός υπολογιστής","Θεώρημα Bayes","Θεωρία Πιθανοτήτων","Ιατρική πληροφορική","Στήριξη αποφάσεων","Τεχνητή διατροφή","Bayes' theorem","Computers","Decision analysis","Medical informatics","Nutrition","Nutritional assessment","Probability Theory","Weight of evidence of asymptoms","Φυσικές Επιστήμες","Επιστήμη Ηλεκτρονικών Υπολογιστών και Πληροφορική","Ιατρική και Επιστήμες Υγείας","Άλλες Ιατρικές Επιστήμες","Natural Sciences","Computer and Information Sciences","Medical and Health Sciences","Other Medical Sciences"],"dc:title":["Η λήψη αντικειμενικών αποφάσεων στην τεχνητή διατροφή με την βοήθεια ηλεκτρονικού υπολογιστή (Computer assisted medical decision making)","Computer assisted medical decision making in nutritional assessment"],"dc:type":["PhD Thesis"]},"updated_at":"2026-07-24T02:25:02Z"}