sentence
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[ "έγκυος", "με", "ταμπόν" ]
[ 0, 0, 8 ]
[ "Το", "αποτέλεσμα", "είναι", "μια", "πυκνή", "ουσία", "που", "μυρίζει", "άσχημα,", "που", "ονομάζεται", "smegma." ]
[ 0, 0, 0, 1, 2, 3, 0, 2, 0, 0, 0, 0 ]
[ "αυτές", "κάτι", "στα", "νεφρά", "Είναι", "οι", "πέτρες", "ή", "άλλο;" ]
[ 1, 0, 0, 2, 0, 0, 3, 0, 0 ]
[ "λάθη", "στη", "γραμματική", "και", "στίξη", "κακή", "γραφή", "κακή", "ορθογραφία" ]
[ 1, 2, 3, 0, 0, 1, 3, 0, 3 ]
[ "για", "τα", "συνηθισμένα", "σημεία", "του", "δέρματος", "πολλοί", "δερματολόγοι", "συμφωνούν", "ότι", "είναι", "τέλεια", "να", "δοκιμάσει", "πάνω", "από", "την", "αντιτρομοκρατική", "θεραπεία", "για", "μερικούς", "μήνες" ]
[ 0, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 7, 0, 0, 0 ]
[ "Ελέγχοντας", "ένα", "επίπεδο", "σιδήρου", "και", "φερριτίνης", "ο", "γιατρός", "σας", "θα", "είναι", "σε", "θέση", "να", "πει", "πόσο", "σίδηρο", "έχετε", "στο", "σώμα", "σας" ]
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[ "έως", "από", "αναφοράς", "εξέταση", "η", "που", "13", "είναι", "Υποθέτοντας", "ότι", "αναφέρεστε", "αίματος", "ταιριάζει", "18", "αριθμό", "της", "εύρος", "στον", "στο", "επειδή", "αιμοσφαιρίνης", "περισσότερο", "αυτή", "σας," ]
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[ "μια", "προσέγγιση", "πολύπλοκα", "θέματα" ]
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[ "Μπορεί", "να", "αισθάνονται", "ζεστά", "στο", "άγγιγμα,", "αλλά", "σπάνια", "είναι", "φαγούρα", "ή", "επώδυνο" ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 0, 4 ]
[ "ζύμης", "ένα", "thrush", "να", "μπορεί", "από", "στόματος", "μια", "φάρμακο", "συνταγογραφηθεί", "λοίμωξη", "για", "του", "αντιμυκητιασικό" ]
[ 3, 5, 3, 0, 0, 0, 1, 1, 7, 0, 3, 0, 0, 6 ]
[ "αρτηριακή", "πίεση", "μπορεί", "μειωθεί", "η", "σας", "να", "έτσι" ]
[ 10, 11, 0, 0, 9, 0, 0, 0 ]
[ "τους", "στομάχι", "για", "κίνδυνο", "το", "δωδεκαδακτυλικούς", "επίσης", "διατρέχουν", "και", "πολύποδες" ]
[ 0, 2, 0, 0, 0, 2, 0, 0, 2, 3 ]
[ "Δεν", "έχω", "συμπτώματα", "ηπατικής", "βλάβης,", "δεν", "έχω", "ναυτία", "κουρασμένη", "κούραση" ]
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[ "dupuytren", "27s" ]
[ 1, 2 ]
[ "εάν", "εμφανιστούν", "συμπτώματα", "μπορεί", "να", "είναι", "παρόμοια", "με", "εκείνα", "χρόνιας", "νεφρικής", "ανεπάρκειας", "νεφρωσικό", "σύνδρομο", "λοίμωξης", "του", "ουροποιητικού", "συστήματος" ]
[ 0, 0, 4, 0, 0, 0, 0, 0, 0, 1, 1, 3, 1, 0, 0, 0, 1, 2 ]
[ "im", "εξαιρετικά", "κλειστοφοβική", "και", "χρειάζεται", "ένα", "mri", "της", "σπονδυλικής", "στήλης" ]
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[ "Μερικοί", "άνθρωποι", "μπορεί", "να", "μην", "έχουν", "συμπτώματα", "άλλοι", "μπορεί", "να", "έχουν", "ήπια", "ερυθρότητα", "και", "παράλυση" ]
[ 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 3, 0, 4 ]
[ "τι", "προκαλεί", "ανεμοβλογιά" ]
[ 0, 0, 4 ]
[ "που", "ιατρική", "από", "σας", "το", "από", "ετήσια", "τα", "υγείας", "περίθαλψη", "5", "60", "πρόγραμμα", "την", "πληρώνει", "από", "για", "σας", "εισοδήματά", "καλύπτεται", "και" ]
[ 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0 ]
[ "-", "Κάνεις", "τα", "κόπρανα", "σου", "μαύρα;", "-", "Όχι." ]
[ 0, 0, 1, 3, 1, 0, 0, 0 ]
[ "Συγχαρητήρια", "για", "την", "εγκυμοσύνη", "σου." ]
[ 0, 0, 1, 0, 0 ]
[ "gerd", "χαλαρότητα", "των", "les" ]
[ 4, 1, 2, 3 ]
[ "υπάρχουν", "αρκετές", "ιατρικές", "παθήσεις", "που", "μπορούν", "να", "προκαλέσουν", "οδονοφάγια" ]
[ 0, 1, 2, 3, 0, 0, 0, 0, 4 ]
[ "σύνδρομο", "ευερέθιστου", "εντέρου", "διάρροιας", "δυσκοιλιότητας" ]
[ 1, 1, 2, 4, 4 ]
[ "Νερό", "γλοιώδη", "απαλλαγή", "από", "το", "πέος" ]
[ 4, 1, 2, 2, 2, 3 ]
[ "Άλλαξε", "επίσης", "τα", "φάρμακά", "μου", "σε", "υδροκοδόνη", "7" ]
[ 0, 0, 0, 0, 0, 0, 8, 0 ]
[ "σπουδαίος.", "το", "ρύσεως,", "να", "όσο", "κανένας", "κύκλους", "εμμήνου", "λίγους", "προτιμούσα", "δυνατόν", "δεν", "έχω", "ήταν", "θα", "Θα" ]
[ 0, 0, 0, 0, 0, 0, 7, 6, 5, 0, 0, 0, 0, 0, 0, 0 ]
[ "Η", "μαμά", "μου", "έλεγξε", "τον", "σφυγμό", "μου", "και", "είπε", "ότι", "δεν", "πειράζει." ]
[ 0, 0, 0, 0, 9, 11, 0, 0, 0, 0, 0, 0 ]
[ "Χρησιμοποίησα", "την", "κρέμα", "μερικές", "φορές", "την", "ημέρα", "για", "μερικές", "εβδομάδες." ]
[ 0, 5, 7, 0, 0, 0, 0, 0, 0, 0 ]
[ "προκαλείται", "από", "το", "αλκοόλ", "επιβραδύνοντας", "τις", "λειτουργίες", "του", "σώματος", "για", "παράδειγμα", "αναπνοή", "καρδιακού", "ρυθμού", "και", "αντανακλαστικού", "gag", "με", "αποτέλεσμα", "δυνητικά", "να", "οδηγήσει", "σε", "πνιγμό", "κώμα", "σταμάτησε", "την", "αναπνοή", "σταμάτησε", "η", "καρδιά", "και", "ο", "θάνατος" ]
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[ "ακόμη", "μπορεί", "τη", "απειλητικές", "οι", "ζωή", "επιπλοκές", "είναι", "μερικές", "Ωστόσο,", "σοβαρές", "πολύ", "για", "και", "και", "φορές", "να" ]
[ 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "κόλλησα", "Μόλις", "χλαμύδια." ]
[ 1, 0, 3 ]
[ "μνήμη", "σκέψη", "προβλήματα", "κατάθλιψης", "και", "ή", "προβλήματα" ]
[ 0, 0, 3, 0, 0, 0, 0 ]
[ "του", "είναι", "πώς", "τι", "και", "γόνατου", "οστεοαρθρίτιδα", "αντιμετωπίζεται" ]
[ 2, 0, 0, 0, 0, 3, 1, 0 ]
[ "Απλά", "ανακατεύετε", "cp", "και", "κουρκουμά", "5050", "σε", "ελαιόλαδο", "και", "μετά", "ανακατεύετε", "με", "πελτέ", "ντομάτας", "και", "το", "αραιώνετε", "με", "ελαιόλαδο", "στην", "αρχή", "ανακατεύοντας", "αυτό", "με", "μια", "ζέστη", "που", "σας", "ταιριάζει", "και", "με", "την", "πάροδο", "του", "χρόνου", "μπορείτε", "να", "αυξήσετε", "σιγά-σιγά", "το", "cp", "και", "το", "κουρκουμάρι" ]
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[ "χρησιμοποιώντας", "αντι-fungle", "κρέμα", "και", "τριπλή", "κρέμα", "αντιβιοτικών", "και", "shes", "χρησιμοποιώντας", "ένα", "θερμαινόμενο", "μαξιλάρι", "για", "τον", "πόνο" ]
[ 0, 6, 7, 0, 5, 7, 6, 0, 0, 0, 5, 6, 7, 0, 1, 3 ]
[ "δεν", "έχουν", "τα", "ίδια", "συμπτώματα", "όλες", "οι", "γυναίκες", "με", "pcos" ]
[ 0, 0, 1, 2, 3, 0, 0, 0, 0, 4 ]
[ "ο", "γενικός", "κανόνας", "είναι", "εάν", "τα", "συμπτώματά", "σας", "είναι", "πάνω", "από", "το", "λαιμό", "αποπνικτική", "μύτη", "φτέρνισμα", "προχωρήστε" ]
[ 0, 0, 0, 0, 0, 1, 3, 0, 0, 0, 0, 1, 2, 3, 0, 3, 0 ]
[ "Οι", "εργαστηριακές", "εργασίες", "γενικά", "αναφέρονται", "στην", "ανάλυση", "αίματος" ]
[ 0, 0, 0, 0, 0, 0, 11, 9 ]
[ "τα", "σημάδια", "της", "τριχόπτωσης", "περιλαμβάνουν", "στους", "άνδρες", "λεπτόνοντας", "τα", "μαλλιά", "στο", "τριχωτό", "της", "κεφαλής", "ένα", "υποχωρητικό", "hairline", "ή", "ένα", "μοτίβο", "σε", "σχήμα", "πέταλου", "που", "αφήνει", "το", "στέμμα", "του", "κεφαλιού", "εκτεθειμένο" ]
[ 0, 0, 0, 3, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 2, 3, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "περπάτημα", "μέτριας", "jogging", "αερόβια", "την", "5", "ημέρες", "για", "λεπτά", "γρήγορα", "ποδηλασία", "30", "αγωνίζονται", "εβδομάδα", "καρδιοπάθειας", "κ.λπ.", "ελλειπτική", "τουλάχιστον" ]
[ 0, 1, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0 ]
[ "6", "ουγγιές", "τσάι", "35", "mg" ]
[ 0, 0, 8, 0, 0 ]
[ "σπίτι." ]
[ 5 ]
[ "μειωμένη", "όρεξη" ]
[ 1, 3 ]
[ "φάρμακα", "αυτών", "μεσολαβητών", "τέτοια", "συμπτώματα" ]
[ 8, 5, 7, 1, 3 ]
[ "Είναι", "η", "που", "τους", "τρελαίνουν", "τους", "για", "γονείς", "αυτή", "ψείρες", "υστερία", "δασκάλους.", "και" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 0, 0 ]
[ "μια", "κινούμενη", "μπότα", "μυϊκή", "ατροφία", "συρρίκνωση" ]
[ 5, 6, 7, 1, 2, 3 ]
[ "οποιαδήποτε", "σημεία", "και", "συμπτώματα", "της", "νόσου" ]
[ 1, 2, 2, 3, 1, 3 ]
[ "μωρό", "αποβολή." ]
[ 3, 3 ]
[ "μαντήλι" ]
[ 4 ]
[ "είναι", "σημαντικό", "να", "σημειωθεί", "ότι", "το", "os", "800/1999vir", "δεν", "θεραπεύει", "ακριβώς", "τη", "γρίπη" ]
[ 0, 0, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0 ]
[ "Αν", "παραμείνει", "σαν", "σκηνή,", "αυτό", "είναι", "σημάδι", "σοβαρής", "αφυδάτωσης." ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 3 ]
[ "Μην", "συμπτώματά", "σταματήσετε", "επειδή", "σας", "ένα", "να", "μόνο", "παίρνετε", "τα", "μόνο", "αντιβιοτικό", "και", "καθαρίζουν" ]
[ 0, 3, 0, 0, 0, 5, 0, 0, 0, 1, 0, 7, 0, 0 ]
[ "Αυτός", "ή", "αυτή", "θα", "σας", "εξετάσει", "και", "θα", "πάρετε", "ένα", "δείγμα", "υγρού", "από", "τον", "κόλπο", "σας" ]
[ 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0 ]
[ "Θα", "σας", "κάνουν", "τελικά", "να", "χρειαστεί", "να", "κάνετε", "μια", "εγχείρηση", "που", "ονομάζεται", "monoloacation", "nissen" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 5, 7, 0, 0, 7, 5 ]
[ "Οι", "διαβίωσης", "συνθήκες", "πιο", "σε", "στενές", "στο", "συχνές", "συνωστισμένες", "κεφάλι", "ψείρες", "είναι" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0 ]
[ "είναι", "εσωτερική", "συνιστάται", "ψάρια", "βαθμούς", "θερμοκρασία", "βαθμούς", "μπριζόλες", "ελάχιστη", "145", "usda", "f", "Το", "f", "145", "ασφαλής", "ψητά" ]
[ 0, 6, 0, 0, 0, 7, 0, 0, 6, 0, 0, 0, 0, 0, 0, 5, 0 ]
[ "Του", "έδωσα", "μείωση", "του", "πυρετού,", "αλλά", "δεν", "φαίνεται", "να", "δουλεύει." ]
[ 0, 5, 7, 0, 0, 0, 0, 0, 0, 0 ]
[ "παρατηρήσετε", "φορές", "την", "όρεξή", "σας", "αλλάζει", "και", "ακολουθείτε", "κατά", "μήκος" ]
[ 0, 0, 1, 2, 0, 3, 0, 0, 0, 0 ]
[ "ιλαράς", "την", "αναπαραγωγική", "οδό,", "μια", "κοινή", "επιπλοκή" ]
[ 4, 1, 2, 3, 1, 2, 3 ]
[ "Είναι", "πιθανό", "ότι", "μου", "το", "προσέλαβε", "αυτό", "ακόμα", "και", "αν", "δεν", "έχω", "hsv", "1" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0 ]
[ "φάρμακα", "να", "πρέπει", "δύο", "ώρες", "12", "λαμβάνονται", "τα", "χωριστά" ]
[ 7, 0, 0, 6, 0, 0, 0, 5, 0 ]
[ "φορούν", "ένα", "αντηλιακό", "ευρύ", "φάσμα", "κάθε", "μέρα" ]
[ 0, 5, 7, 0, 7, 0, 0 ]
[ "αμυγδαλιίτιδα", "στρεπτόκοκκο", "ένα", "από", "που", "βακτηριακό", "απαιτεί", "Ωστόσο,", "να", "προκληθεί", "είναι", "μπορεί", "που", "αντιβιοτικό" ]
[ 4, 4, 5, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 7 ]
[ "ένα", "ήπιο", "κρυολόγημα", "ο", "βήχας" ]
[ 1, 2, 3, 1, 3 ]
[ "η", "απολέπιση", "θα", "βοηθήσει", "στην", "ελαχιστοποίηση", "της", "επανάληψης", "των", "μαύρων", "κεφαλών" ]
[ 4, 4, 0, 0, 0, 0, 1, 2, 2, 3, 3 ]
[ "οστεοαρθρίτιδας", "πρωτοπαθή", "οστεοαρθρίτιδα" ]
[ 4, 1, 3 ]
[ "διάφορα", "προϊόντα" ]
[ 5, 7 ]
[ "πρώτο", "μήνα", "δεδομένου", "των", "στον", "παρέχουν", "εάν", "χάπια", "σας,", "αντισυλληπτική", "ότι", "απίθανο", "συσκευασίας", "μήνα", "τα", "πρώτο", "τον", "περισσότερα", "είστε", "χαπιών", "προστασία", "έγκυος,", "μετά", "πρώτης", "ότι", "ήταν", "φαίνεται", "δεν" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 7, 0, 0, 0, 0, 0, 0, 0 ]
[ "ένα", "τεστ", "ναρκωτικών" ]
[ 9, 11, 11 ]
[ "δύο", "μικρές", "λευκές", "κουκκίδες" ]
[ 1, 2, 2, 3 ]
[ "ένα", "παγκρεατικό", "ψευδοκύστ", "μπορεί", "επίσης", "να", "συμβεί", "μετά", "από", "τραύμα", "στην", "κοιλιακή", "χώρα", "και", "σε", "κάποιον", "με", "χρόνια", "παγκρεατίτιδα" ]
[ 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 2, 0, 3, 0, 0, 0, 0, 1, 3 ]
[ "Ο", "πόνος", "λόγω", "τραύματος", "χρειάζεται", "χρόνο", "για", "να", "επουλωθεί" ]
[ 4, 4, 0, 4, 0, 0, 0, 0, 0 ]
[ "συμπτώματα", "διατροφικής", "διαταραχής" ]
[ 4, 2, 3 ]
[ "Χρησιμοποιώ", "θρομιμαζόλη", "πρόσωπό", "μου", "β-μεθασόνη", "κρέμα", "που", "στο", "γενταμικίνη", "περιέχει", "μια", "και" ]
[ 0, 7, 7, 6, 5, 6, 0, 6, 8, 0, 5, 0 ]
[ "ρίγη", "σκούρα", "ούρα", "διευρυμένη", "σπλήνα", "κόπωση", "πυρετός", "ωχρό", "δέρμα", "χρώμα", "ωχρό", "χρώμα", "ωχρότητα", "ταχεία", "καρδιακή", "ανεπάρκεια", "δύσπνοια", "κίτρινο", "χρώμα", "του", "δέρματος", "ίκτερος" ]
[ 4, 1, 3, 1, 2, 3, 4, 1, 3, 1, 0, 3, 0, 1, 0, 3, 0, 0, 0, 0, 0, 3 ]
[ "ποια", "είναι", "τα", "συμπτώματα", "του", "έρπητα", "ζωστήρα" ]
[ 0, 0, 1, 3, 0, 1, 3 ]
[ "πρωτογενή", "κίρρωση", "χολική", "τι", "την", "προκαλεί" ]
[ 0, 3, 2, 0, 0, 0 ]
[ "καταστροφή", "ήπια", "πιο", "μορφή", "προκαλεί", "ασυμβίβαστο", "του,", "Στην", "το", "των", "αιμοσφαιρίων", "την", "ερυθρών" ]
[ 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 1, 2 ]
[ "ο", "σπασμός", "εμφανίζεται", "συχνά", "σε", "στεφανιαίες", "αρτηρίες", "που", "δεν", "έχουν", "σκληρυνθεί", "λόγω", "συσσώρευσης", "πλάκας", "αθηροσκλήρωση" ]
[ 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 3 ]
[ "αν", "εξαιρετικά", "μια", "η", "θα", "στόματος", "επένδυση", "παίρνει", "σας", "εκτός", "ο", "στόμα", "αντιμετωπιστεί", "ότι", "κίνδυνος", "έτσι,", "στόμα", "υπάρχει", "σας", "στόμα", "που", "εσωτερική", "είναι", "ελπίζω", "στο", "χαμηλός", "έναν", "Επίσης,", "ή", "σάλιο", "με", "και", "συμβεί", "αιμορραγίες", "ή", "έλκος", "να", "μάσημα", "δύσκολο", "κουβά", "hiv", "τσίχλα", "δεν", "κάποιος", "είτε", "είναι", "στο", "με", "του", "στο", "αιμορραγία" ]
[ 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 3, 0, 0, 0, 0, 3, 0, 2, 3, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 2, 0, 0, 0, 2 ]
[ "πλευρά", "μεγάλο", "ένα", "του", "Έχω", "τι", "κάτω", "θα", "μπορούσε", "να", "εξόγκωμα", "μου", "στην", "είναι", "χείλους", "δεξιά" ]
[ 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0 ]
[ "της", "Η", "νέας", "εμφύτευση", "προετοιμασία", "στην", "μήτρας", "προγεστερόνη", "επένδυση", "μιας", "εγκυμοσύνης", "για", "σταθεροποιεί", "πιθανή", "την" ]
[ 0, 0, 2, 8, 0, 0, 7, 8, 0, 1, 3, 0, 0, 0, 5 ]
[ "τραμαδόλη", "άλλες", "συνταγές", "οπιούχων" ]
[ 8, 5, 7, 7 ]
[ "επέμβαση,", "moyamoya", "αρτηριών", "πλειοψηφία", "προοδευτικής", "χειρουργική", "νόσο", "λόγω", "ατόμων", "των", "βιώσει", "της", "με", "επεισόδια", "στένωσης", "πολλαπλά", "των", "πτώση", "χωρίς", "η", "διανοητική", "και", "θα", "εγκεφαλικά" ]
[ 8, 1, 3, 0, 2, 0, 3, 0, 0, 0, 0, 1, 0, 3, 2, 1, 2, 0, 0, 0, 1, 0, 0, 0 ]
[ "χάπια", "εικονικού", "φαρμάκου." ]
[ 7, 5, 5 ]
[ "το", "επιπλέον", "λάδι", "ακμή" ]
[ 5, 6, 7, 4 ]
[ "λακτάσης", "είναι", "διαθέσιμα", "καψάκια", "ενζύμου", "ή", "δισκία", "λακτάσης", "με", "γάλα", "που", "περιέχουν", "τρόφιμα" ]
[ 9, 0, 0, 5, 0, 0, 5, 7, 0, 0, 0, 0, 0 ]
[ "διαδικασία", "υπέρβαση", "είναι", "διαπροσωπικών", "τους", "αριθμό", "μικρό", "διαταραχής", "θριάμβων", "και", "η", "βασίζεται", "κοινωνικής", "Αλλά", "μια", "επιτυχία", "ένα", "αγχώδους", "της", "στην", "που", "περιλαμβάνει" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0 ]
[ "είναι", "καλή", "συστάσεις", "επαρκή", "ένα", "σύμφωνα", "γαστρεντερικού", "τις", "να", "ποτό", "γιατρού", "αίματος", "του", "υγρά", "εργασίες", "gi", "πολυβιταμινούχο", "να", "κάνετε", "πάρετε", "και", "με", "σας", "ιδέα", "τις" ]
[ 0, 0, 0, 0, 5, 0, 0, 0, 0, 7, 0, 9, 0, 0, 11, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "τα", "δύο", "φάρμακα" ]
[ 5, 6, 7 ]
[ "αντιβιοτικά", "ή", "στρες" ]
[ 8, 0, 4 ]
[ "μάθετε", "αν", "χρειάζεστε", "πρόληψη", "της", "ελονοσίας" ]
[ 0, 0, 0, 7, 0, 7 ]
[ "είναι", "πολύ", "σημαντικό", "να", "χρησιμοποιούνται", "όλα", "τα", "φάρμακα", "για", "βρέφη", "ακριβώς", "όπως", "συνταγογραφήθηκε" ]
[ 0, 0, 0, 0, 0, 5, 0, 7, 0, 0, 0, 0, 0 ]
[ "τυχόν", "αλλαγές", "στα", "έντερα" ]
[ 1, 2, 2, 3 ]
[ "φάρμακα", "το", "και", "αυτό", "μέσα", "ανάγνωση", "μια", "γεια", "πολλή", "καλή", "βοήθεια", "από", "σας", "site", "έχουν", "χωρίς" ]
[ 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "εύθραυστος", "ιστός" ]
[ 1, 3 ]
[ "αιμορραγία", "παχέος", "το", "αρχαιότερο", "να", "σημάδι", "είναι", "μπορεί", "του", "εντέρου", "καρκίνου" ]
[ 4, 1, 0, 0, 0, 0, 0, 0, 0, 1, 3 ]
[ "μπορούν", "συνταγές", "να", "χρησιμοποιηθούν", "για", "βοηθήσει", "κατά", "να", "υπάρχουν", "μήκος", "κρέμες", "αν", "δεν", "που", "στεροειδών" ]
[ 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 6 ]
[ "συμπτώματα", "πυρετό", "δώσετε", "ανεμοβλογιά", "δεν", "εάν", "άρρωστο", "για", "ένα", "ή", "φάρμακο", "μπορεί", "για", "παραπονεθεί", "να", "να", "επιλέξετε", "παιδί", "μην", "δράσει", "με" ]
[ 4, 4, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]

Greek NER dataset

Acknowledgement

This dataset had been created as part of joint research of HUMADEX research group (https://www.linkedin.com/company/101563689/) and has received funding by the European Union Horizon Europe Research and Innovation Program project SMILE (grant number 101080923) and Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks, project BosomShield ((rant number 101073222). Responsibility for the information and views expressed herein lies entirely with the authors. Authors: dr. Izidor Mlakar, Rigon Sallauka, dr. Umut Arioz, dr. Matej Rojc

Dataset Building

Data Integration and Preprocessing

We begin by merging two distinct datasets of English medical texts. This step ensures a robust and diverse corpus, combining the strengths of both datasets. Following the integration, we preprocess the texts to clean the data, which includes removal of strings that do not contain relevant information. This preprocessing step is crucial to ensure the texts are in an optimal format for subsequent annotation.

The data underwent a preprocessing process.

  1. Data Cleaning: Since our dataset consisted of question-answer pairs between a user and an assistant, some extraneous text could be removed without losing relevant information.

    • In the Kabatubare/autotrain-data-1w6s-u4vt-i7yo dataset, we removed the following strings:
      • Human:

      • Assistant:

      • \n (newline characters)

      • \t (tab characters)

      • Hyphens between words (-) were replaced with a single space.

    • In the s200862/medical_qa_meds dataset, we removed:
      • [INST]
      • [/INST]
      • <s>
      • </s>
      • \n (newline characters)
      • \t (tab characters)
  2. Punctuation Removal: All punctuation marks were removed from the text to ensure consistency.

  3. Lowercasing: Finally, the entire dataset was converted to lowercase to standardize the text.

Annotation with Stanza's i2b2 Clinical Model

The preprocessed English texts are then annotated using Stanza's i2b2 Clinical Model. This model is specifically designed for clinical text processing, and it annotates each text with three labels: - PROBLEM: Includes diseases, symptoms, and medical conditions. - TEST: Represents diagnostic procedures and laboratory tests.

TREATMENT: Covers medications, therapies, and other medical interventions.

This annotation step is essential for creating a labeled dataset that serves as the foundation for training and evaluating Named Entity Recognition (NER) models.

We used Stanza's clinical-domain NER system, which contains a general-purpose NER model trained on the 2010 i2b2/VA dataset. This model efficiently extracts entities related to problems, tests, and treatments from various types of clinical notes.

Tag encodings:

  • "O": 0
  • "B-PROBLEM": 1
  • "I-PROBLEM": 2
  • "E-PROBLEM": 3
  • "S-PROBLEM": 4
  • "B-TREATMENT": 5
  • "I-TREATMENT": 6
  • "E-TREATMENT": 7
  • "S-TREATMENT": 8
  • "B-TEST": 9
  • "I-TEST": 10
  • "E-TEST": 11
  • "S-TEST": 12

Translation into Greek

The annotated English dataset is translated into Greek: Model name: Helsinki-NLP/opus-mt-en-el Model was developed by Language Technology Research Group at the University of Helsinki. Model Type is Translation.

Word Alignment

Model: aneuraz/awesome-align-with-co

This method is for extracting alignments between words in parallel sentences using contextual word embeddings from models like BERT . Main processing steps:

  1. Contextual Word Embeddings: Powerful models like BERT capture the meaning of words based on their context in a sentence. These models can be used to generate numerical representations (embeddings) for each word in a sentence.

  2. Alignment Scores: The method calculates alignment scores between words in two parallel sentences (sentences in different languages that mean the same thing). Two approaches are used:

    • Probability Thresholding: This method uses a similarity matrix based on the dot product of word embeddings. It then applies a function (like softmax) to turn similarities into probabilities and identifies high-probability pairs as aligned.
    • Optimal Transport: This approach views alignment as a transportation problem, where the goal is to move "probability mass" between words in a way that minimizes cost (distance between word embeddings). The resulting matrix shows likely alignments.
  3. Bidirectional Alignments: The method considers alignments in both directions (source to target and target to source). The final alignment is obtained by finding the intersection of alignments in both directions.

  4. Subword Handling: Since some models work with subwords (parts of words), the method considers two words aligned if any of their subwords are aligned.

Overall, this approach leverages contextual word embeddings and different techniques to find corresponding words between sentences in different languages.

Data Augmentation

We performed data augmentation to enhance the diversity and robustness of the training data. The augmentation process involved two main strategies:

  • Sentence Reordering: Words within each sentence were reordered to create new variations of the same sentence structure. This method increases the variability of the dataset, enabling the model to generalize better to different sentence formations.
  • Entity Extraction: All words within each sentence that were annotated with non-"O" labels (i.e., labeled as PROBLEM, TEST, or TREATMENT) were extracted and used to generate new sentences. These sentences were then added back into the dataset, ensuring that the model would encounter more examples of key medical entities during training.
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