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Ana ɗaukar hakora a matsayin mafi daidaiton nunin shekarun jikin ɗan adam kuma galibi ana amfani da su wajen tantance shekarun bincike.Mun yi nufin inganta ƙididdiga na tushen haƙoran haƙora na tushen bayanai ta hanyar kwatanta daidaiton ƙididdiga da aikin rarrabuwar kawuna na shekaru 18 tare da hanyoyin gargajiya da ƙididdiga na tushen bayanan hakar ma'adinai.An tattara jimlar faifan radiyo 2657 daga mutanen Koriya da Japan masu shekaru 15 zuwa 23.An raba su zuwa tsarin horarwa, kowanne yana ɗauke da faifan rediyo na Koriya 900, da kuma tsarin gwaji na ciki mai ɗauke da hotuna 857 na Japan.Mun kwatanta daidaiton rarrabuwar kawuna da inganci na hanyoyin gargajiya tare da tsarin gwaji na ƙirar haƙar ma'adinai.Daidaitaccen hanyar gargajiya akan saitin gwaji na ciki ya ɗan fi girma fiye da na samfurin hakar ma'adinan bayanai, kuma bambanci kaɗan ne (ma'anar cikakkiyar kuskure <0.21 shekaru, tushen yana nufin kuskuren murabba'in <0.24 shekaru).Ayyukan rarrabuwar kawuna don yankewar shekaru 18 shima yayi kama da tsakanin hanyoyin gargajiya da samfuran hakar bayanai.Don haka, hanyoyin gargajiya za a iya maye gurbinsu da samfuran haƙar ma'adinan bayanai yayin yin kima da shekarun bincike ta amfani da balaga na molars na biyu da na uku a cikin samari da matasa na Koriya.
Ana amfani da ƙididdigar shekarun haƙori a ko'ina a cikin likitancin likita da likitan hakora na yara.Musamman, saboda babban alaƙa tsakanin shekarun ƙididdiga da haɓakar haƙori, ƙididdige shekaru ta matakan haɓakar hakori muhimmin ma'auni ne don tantance shekarun yara da matasa1,2,3.Duk da haka, ga matasa, kimanta shekarun hakori bisa ga balagagge hakori yana da iyaka saboda girman haƙori ya kusa cika, ban da molar na uku.Manufar doka ta kayyade shekarun matasa da samari ita ce samar da ingantattun ƙididdiga da shaidar kimiyya na ko sun kai shekarun girma.A cikin aikin likitancin doka na matasa da matasa a Koriya, an kiyasta shekaru ta hanyar amfani da hanyar Lee, kuma an yi la'akari da matakin doka na shekaru 18 bisa ga bayanan da Oh et al 5 ya ruwaito.
Koyon inji wani nau'in hankali ne na wucin gadi (AI) wanda ke koyo akai-akai tare da rarraba bayanai masu yawa, yana magance matsalolin da kansa, kuma yana tafiyar da shirye-shiryen bayanai.Koyon na'ura na iya gano ɓoyayyun alamu masu amfani a cikin manyan ɗimbin bayanai6.Sabanin haka, hanyoyin gargajiya, waɗanda suke da ƙwaƙƙwaran aiki da ɗaukar lokaci, na iya samun iyakancewa yayin da ake mu'amala da manyan bayanai masu rikitarwa waɗanda ke da wahalar aiwatarwa da hannu7.Saboda haka, an gudanar da bincike da yawa kwanan nan ta amfani da sabbin fasahohin kwamfuta don rage kurakuran ɗan adam da aiwatar da ingantaccen bayanai masu yawa8,9,10,11,12.Musamman, an yi amfani da zurfin ilmantarwa sosai a cikin nazarin hoton likita, kuma hanyoyi daban-daban don ƙididdige shekaru ta hanyar nazarin radiyo ta atomatik an ba da rahoton don inganta daidaito da ingancin ƙimar shekaru13,14,15,16,17,18,19,20 .Misali, Halabi et al 13 sun ɓullo da na'urar koyon na'ura akan hanyoyin sadarwa na jijiyoyi (CNN) don ƙididdige shekarun kwarangwal ta amfani da radiyo na hannun yara.Wannan binciken ya ba da shawarar samfurin da ke amfani da koyo na na'ura zuwa hotunan likita kuma yana nuna cewa waɗannan hanyoyin zasu iya inganta daidaiton bincike.Li et al14 an kiyasta shekaru daga hotunan X-ray na pelvic ta amfani da CNN mai zurfi koyo da kuma kwatanta su da sakamakon koma baya ta amfani da kimanta matakin ossification.Sun gano cewa ƙirar CNN mai zurfi ta ilmantarwa ta nuna aikin ƙididdige shekaru iri ɗaya kamar tsarin koma baya na gargajiya.Binciken Guo et al. [15] ya kimanta aikin rarrabuwar juriya ga shekarun fasahar CNN bisa la'akari da hotunan hakora, kuma sakamakon samfurin CNN ya tabbatar da cewa ɗan adam ya zarce aikin tantance shekarunsa.
Yawancin karatu akan ƙiyasin shekaru ta amfani da koyon injin suna amfani da hanyoyin koyo mai zurfi13,14,15,16,17,18,19,20.An ba da rahoton kiyasin shekaru bisa zurfin ilmantarwa ya fi daidai fiye da hanyoyin gargajiya.Koyaya, wannan hanyar tana ba da ɗan ƙaramin zarafi don gabatar da tushen kimiyya don ƙididdige shekaru, kamar alamun shekarun da aka yi amfani da su a cikin ƙididdiga.Akwai kuma takaddama a shari’a kan wanda ya gudanar da binciken.Don haka, ƙididdige shekaru bisa zurfin ilmantarwa yana da wahala a karɓa daga hukumomin gudanarwa da na shari'a.Ma'adinin bayanai (DM) wata dabara ce da za ta iya gano ba kawai ake tsammani ba har ma da bayanan da ba zato ba tsammani a matsayin hanya don gano alaƙa mai amfani tsakanin adadi mai yawa na bayanai6,21,22.Ana amfani da koyan na'ura sau da yawa wajen haƙar ma'adinan bayanai, kuma duka haƙar ma'adinai da na'ura suna amfani da maɓalli iri ɗaya don gano alamu a cikin bayanai.Ƙimar shekaru ta amfani da haɓakar haƙori ya dogara ne akan kimantawar mai jarrabawa na balagaggen haƙoran da aka yi niyya, kuma ana bayyana wannan kimar a matsayin mataki na kowane haƙoran da aka yi niyya.Ana iya amfani da DM don nazarin alaƙa tsakanin matakin kimar hakori da ainihin shekaru kuma yana da yuwuwar maye gurbin ƙididdigar ƙididdiga na gargajiya.Don haka, idan muka yi amfani da dabarun DM zuwa kimanta shekaru, za mu iya aiwatar da koyon injina a cikin ƙimar shekarun bincike ba tare da damuwa game da alhaki na doka ba.An buga nazarin kwatance da yawa akan hanyoyin da za a bi zuwa hanyoyin gargajiya na gargajiya da aka yi amfani da su a aikin bincike da hanyoyin tushen EBM don tantance shekarun haƙori.Shen et al23 ya nuna cewa samfurin DM ya fi daidai fiye da tsarin Camerer na gargajiya.Galibourg et al24 sun yi amfani da hanyoyi daban-daban na DM don tsinkayar shekaru bisa ga ma'auni na Demirdjian25 kuma sakamakon ya nuna cewa hanyar DM ta wuce hanyoyin Demirdjian da Willems wajen kimanta shekarun yawan mutanen Faransa.
Don ƙididdige shekarun haƙori na samari da matasa na Koriya, Hanyar Lee ta 4 ana amfani da ita sosai a cikin aikin bincike na Koriya.Wannan hanyar tana amfani da bincike na ƙididdiga na gargajiya (kamar koma baya da yawa) don bincika alaƙar batutuwan Koriya da shekarun ƙididdiga.A cikin wannan binciken, hanyoyin tantance shekarun da aka samu ta amfani da hanyoyin ƙididdiga na gargajiya an bayyana su da “hanyoyin gargajiya”.Hanyar Lee hanya ce ta gargajiya, kuma Oh et al ya tabbatar da daidaitonsa.5;duk da haka, amfani da ƙididdige shekaru bisa tsarin DM a cikin aikin bincike na Koriya har yanzu abin tambaya ne.Manufarmu ita ce a kimiyance ta tabbatar da yuwuwar amfanin kimar shekaru bisa tsarin DM.Manufar wannan binciken shine (1) don kwatanta daidaiton nau'ikan DM guda biyu a kimanta shekarun hakori da (2) kwatanta aikin rarrabuwa na ƙirar 7 DM a cikin shekaru 18 da waɗanda aka samu ta amfani da hanyoyin ƙididdiga na al'ada Balaga na biyu da kuma molars na uku a duka muƙamuƙi.
Ana nuna ma'ana da daidaitattun sauye-sauye na shekarun ƙididdiga ta mataki da nau'in haƙori akan layi a cikin Ƙarin Tebura S1 (saitin horo), Ƙarin Tebura S2 (saitin gwajin ciki), da Ƙarin Tebura S3 (saitin gwaji na waje).Ƙimar kappa don amincin intra- da interobserver da aka samu daga tsarin horo sun kasance 0.951 da 0.947, bi da bi.Ana nuna ƙimar P da tazarar amincewa 95% don ƙimar kappa a cikin ƙarin tebur S4 akan layi.An fassara ƙimar kappa a matsayin "kusan cikakke", daidai da ƙa'idodin Landis da Koch26.
Lokacin kwatanta ma'anar cikakken kuskure (MAE), hanyar gargajiya ta ɗan fi ƙarfin ƙirar DM ga kowane jinsi kuma a cikin saitin gwajin namiji na waje, ban da multilayer perceptron (MLP).Bambanci tsakanin samfurin gargajiya da samfurin DM akan tsarin gwajin MAE na ciki shine 0.12-0.19 shekaru ga maza da 0.17-0.21 shekaru ga mata.Don baturin gwajin waje, bambance-bambancen sun fi ƙanƙanta (shekaru 0.001-0.05 ga maza da shekaru 0.05-0.09 na mata).Bugu da ƙari, tushen ma'anar kuskuren murabba'i (RMSE) ya ɗan ragu kaɗan fiye da hanyar gargajiya, tare da ƙananan bambance-bambance (0.17-0.24, 0.2-0.24 don saitin gwajin ciki na maza, da 0.03-0.07, 0.04-0.08 don saitin gwajin waje).).MLP yana nuna kyakkyawan aiki fiye da Single Layer Perceptron (SLP), sai dai a yanayin saitin gwajin waje na mace.Don MAE da RMSE, saitin gwajin waje yana da maki sama da tsarin gwajin ciki don duk jinsi da ƙira.Ana nuna duk MAE da RMSE a cikin Tebur 1 da Hoto 1.
MAE da RMSE na al'ada da kuma bayanan hakar ma'adinan regression.Ma'anar cikakken kuskure MAE, tushen ma'anar kuskure murabba'i RMSE, Layer perceptron SLP, multilayer perceptron MLP, hanyar CM na gargajiya.
Ayyukan rarrabuwa (tare da yankewa na shekaru 18) na al'ada da ƙirar DM an nuna su dangane da azanci, ƙayyadaddun ƙayyadaddun ƙima, ƙimar tsinkaya mai kyau (PPV), ƙimar tsinkaya mara kyau (NPV), da yanki a ƙarƙashin madaidaicin yanayin aiki mai karɓa (AUROC) 27 (Table 2, Hoto 2 da Ƙarin Hoto na 1 akan layi).Dangane da hankalin batirin gwajin ciki, hanyoyin gargajiya sun fi kyau a tsakanin maza kuma mafi muni a tsakanin mata.Koyaya, bambancin aikin rarrabawa tsakanin hanyoyin gargajiya da SD shine 9.7% na maza (MLP) kuma kawai 2.4% na mata (XGBoost).Daga cikin nau'ikan DM, koma baya na logistic (LR) ya nuna mafi kyawun hankali a cikin jinsin biyu.Game da ƙayyadaddun tsarin gwajin ciki, an lura cewa samfuran SD guda huɗu sun yi kyau a cikin maza, yayin da ƙirar gargajiya ta fi kyau a cikin mata.Bambance-bambancen aikin rarrabuwa ga maza da mata shine 13.3% (MLP) da 13.1% (MLP), bi da bi, yana nuna cewa bambancin aikin rarrabuwa tsakanin samfuran ya wuce hankali.Daga cikin samfuran DM, na'ura mai ba da tallafi (SVM), bishiyar yanke shawara (DT), da ƙirar gandun daji (RF) bazuwar sun yi mafi kyau tsakanin maza, yayin da ƙirar LR ta yi mafi kyau a tsakanin mata.AUROC na ƙirar gargajiya da duk samfuran SD sun fi 0.925 (k-kusa maƙwabci (KNN) a cikin maza), yana nuna kyakkyawan aikin rarrabuwa a cikin nuna wariya ga samfuran 18 mai shekaru28.Don saitin gwajin waje, an sami raguwar aikin rarrabuwa dangane da hankali, ƙayyadaddun ƙayyadaddun bayanai da AUROC idan aka kwatanta da saitin gwajin ciki.Bugu da ƙari, bambanci a cikin hankali da ƙayyadaddun ƙayyadaddun ƙayyadaddun ayyuka na rarrabuwa na mafi kyawun samfura da mafi muni sun kasance daga 10% zuwa 25% kuma ya fi girma fiye da bambanci a cikin saitin gwajin ciki.
Hankali da ƙayyadaddun samfuran rarraba bayanan ma'adinai idan aka kwatanta da hanyoyin gargajiya tare da yankewar shekaru 18.KNN k mafi kusa, SVM goyon bayan vector inji, LR logistic koma baya, DT yanke shawara itace, RF bazuwar gandun daji, XGB XGBoost, MLP multilayer perceptron, gargajiya CM Hanyar.
Mataki na farko a cikin wannan binciken shine kwatanta daidaiton ƙididdigar shekarun hakori da aka samu daga nau'ikan DM guda bakwai tare da waɗanda aka samu ta amfani da koma bayan al'ada.MAE da RMSE an kimanta su a cikin gwaje-gwaje na ciki don duka jinsin, kuma bambanci tsakanin hanyar gargajiya da samfurin DM ya kasance daga 44 zuwa 77 kwanaki don MAE kuma daga 62 zuwa 88 kwanaki don RMSE.Ko da yake hanyar gargajiya ta ɗan fi daidai a cikin wannan binciken, yana da wuya a kammala ko irin wannan ɗan ƙaramin bambanci yana da mahimmanci na asibiti ko a aikace.Waɗannan sakamakon suna nuna cewa daidaiton ƙimar shekarun hakori ta amfani da ƙirar DM kusan iri ɗaya ne da na hanyar gargajiya.Kwatancen kai tsaye tare da sakamakon binciken da ya gabata yana da wahala saboda babu wani binciken da ya kwatanta daidaiton samfuran DM tare da hanyoyin ƙididdiga na al'ada ta amfani da dabarar rikodin haƙora a cikin kewayon shekaru iri ɗaya kamar a cikin wannan binciken.Galibourg et al24 sun kwatanta MAE da RMSE tsakanin hanyoyin gargajiya guda biyu (Demirjian method25 da Willems method29) da 10 DM model a cikin yawan Faransanci masu shekaru 2 zuwa 24 shekaru.Sun bayar da rahoton cewa duk samfuran DM sun fi dacewa fiye da hanyoyin gargajiya, tare da bambance-bambancen 0.20 da 0.38 a cikin MAE da 0.25 da 0.47 shekaru a RMSE idan aka kwatanta da hanyoyin Willems da Demirdjian, bi da bi.Bambance-bambancen da ke tsakanin tsarin SD da hanyoyin gargajiya da aka nuna a cikin binciken Halibourg ya yi la'akari da rahotanni masu yawa30,31,32,33 cewa hanyar Demirdjian ba ta ƙididdige yawan shekarun haƙori a cikin al'ummomi ban da ƴan ƙasar Faransa na Kanada waɗanda binciken ya dogara akan su.a cikin wannan binciken.Tai et al.Sun ba da rahoton cewa MLP yana da daidaito mafi girma fiye da hanyoyin gargajiya.Bambanci tsakanin hanyar Demirdjian da hanyar gargajiya shine <0.32 shekaru, kuma hanyar Willems shine shekaru 0.28, wanda yayi kama da sakamakon binciken yanzu.Sakamakon waɗannan karatun da suka gabata24,34 kuma sun yi daidai da sakamakon binciken da aka yi a yanzu, kuma daidaitattun shekarun ƙididdiga na ƙirar DM da hanyar gargajiya suna kama da juna.Duk da haka, bisa ga sakamakon da aka gabatar, za mu iya kawai ƙaddamar da hankali cewa yin amfani da samfurori na DM don kimanta shekaru na iya maye gurbin hanyoyin da ake da su saboda rashin daidaituwa da nazarin binciken da suka gabata.Ana buƙatar karatun bin diddigin ta amfani da samfurori mafi girma don tabbatar da sakamakon da aka samu a cikin wannan binciken.
Daga cikin binciken da aka gwada ingancin SD a kimanta shekarun hakori, wasu sun nuna daidaito mafi girma fiye da bincikenmu.Stepanovsky et al 35 sun yi amfani da nau'ikan SD na 22 zuwa radiyon panoramic na mazauna Czech 976 masu shekaru 2.7 zuwa 20.5 kuma sun gwada daidaiton kowane samfurin.Sun kimanta ci gaban jimillar 16 na sama da na hagu na hakora na dindindin ta amfani da ka'idojin rarrabuwa da Moorrees et al 36 suka gabatar.MAE ya fito daga 0.64 zuwa 0.94 shekaru kuma RMSE ya fito daga 0.85 zuwa 1.27 shekaru, waɗanda suka fi dacewa fiye da nau'in DM guda biyu da aka yi amfani da su a cikin wannan binciken.Shen et al23 sun yi amfani da hanyar Cameriere don ƙididdige shekarun hakori na hakora bakwai na dindindin a cikin mandible na hagu a mazauna gabashin kasar Sin masu shekaru 5 zuwa 13 da kuma kwatanta shi da shekarun da aka kiyasta ta amfani da regression linear, SVM da RF.Sun nuna cewa duk nau'ikan DM guda uku suna da daidaito mafi girma idan aka kwatanta da tsarin Cameriere na gargajiya.MAE da RMSE a cikin binciken Shen sun kasance ƙasa da waɗanda ke cikin ƙirar DM a cikin wannan binciken.Ƙarfafa daidaito na binciken da Stepanovsky et al.35 da Shen et al.23 na iya zama saboda haɗa ƙananan batutuwa a cikin samfuran binciken su.Saboda ƙididdigar shekaru ga mahalarta masu haɓaka haƙora sun zama mafi daidai yayin da adadin haƙoran ke ƙaruwa yayin haɓaka haƙori, ana iya lalata daidaiton hanyar ƙididdige shekarun da aka samu lokacin da mahalarta binciken ke ƙanana.Bugu da ƙari, kuskuren MLP a kimanta shekarun ya ɗan ƙanƙanta da na SLP, ma'ana MLP ya fi SLP daidai.Ana ɗaukar MLP mafi ɗanɗano don kimanta shekaru, maiyuwa saboda ɓoyayyun yadudduka a cikin MLP38.Koyaya, akwai keɓance ga samfuran waje na mata (SLP 1.45, MLP 1.49).Gano cewa MLP ya fi SLP daidai a kimanta shekaru yana buƙatar ƙarin nazari na baya.
An kwatanta aikin rarrabuwa na ƙirar DM da kuma hanyar gargajiya a iyakar shekaru 18.Duk samfuran SD da aka gwada da hanyoyin gargajiya akan saitin gwaji na ciki sun nuna a zahiri matakan karɓuwa na wariya ga samfurin ɗan shekara 18.Hankali ga maza da mata ya fi 87.7% da 94.9%, bi da bi, kuma ƙayyadaddun ya fi 89.3% da 84.7%.AUROC na duk samfuran da aka gwada suma sun wuce 0.925.Zuwa iyakar iliminmu, babu wani binciken da ya gwada aikin ƙirar DM don rarrabuwar shekaru 18 dangane da balaga haƙora.Za mu iya kwatanta sakamakon wannan binciken tare da aikin rarrabuwa na ƙirar ilmantarwa mai zurfi akan faifan rediyo.Guo et al.15 sun ƙididdige aikin rarrabuwa na ƙirar ilmantarwa mai zurfi na tushen CNN da kuma hanyar jagora bisa hanyar Demirjian don ƙayyadaddun shekaru.Hankali da ƙayyadaddun hanyar jagora sun kasance 87.7% da 95.5%, bi da bi, kuma hankali da ƙayyadaddun tsarin CNN ya wuce 89.2% da 86.6%, bi da bi.Sun kammala cewa tsarin ilmantarwa mai zurfi na iya maye gurbin ko wuce kima ta hannu wajen rarraba iyakokin shekaru.Sakamakon wannan binciken ya nuna irin wannan aikin rarrabawa;An yi imanin cewa rarrabuwa ta amfani da samfuran DM na iya maye gurbin hanyoyin ƙididdiga na al'ada don kimanta shekaru.Daga cikin samfurori, DM LR shine mafi kyawun samfurin dangane da hankali ga samfurin namiji da ƙwarewa da kuma ƙayyadaddun samfurin mace.LR yana matsayi na biyu a keɓancewa ga maza.Haka kuma, ana ɗaukar LR a matsayin ɗaya daga cikin mafi kyawun ƙirar DM35 mai sauƙin amfani kuma ba shi da rikitarwa kuma yana da wahalar sarrafawa.Dangane da waɗannan sakamakon, an ɗauki LR a matsayin mafi kyawun ƙirar yanke yanke ga yara masu shekaru 18 a cikin al'ummar Koriya.
Gabaɗaya, daidaiton ƙiyasin shekaru ko aikin rarrabuwa akan saitin gwajin waje ya kasance mara kyau ko ƙasa idan aka kwatanta da sakamakon kan saitin gwajin ciki.Wasu rahotanni sun nuna cewa daidaito ko inganci yana raguwa lokacin da aka yi amfani da kiyasin shekaru dangane da yawan jama'ar Koriya ga jama'ar Japan5,39, kuma an sami irin wannan tsari a cikin binciken na yanzu.An kuma lura da wannan yanayin lalacewa a cikin ƙirar DM.Don haka, don ƙididdige shekaru daidai, ko da lokacin amfani da DM a cikin tsarin bincike, hanyoyin da aka samo daga bayanan yawan jama'a, kamar hanyoyin gargajiya, ya kamata a fifita su5,39,40,41,42.Tun da yake ba a sani ba ko ƙirar ilmantarwa mai zurfi za su iya nuna irin wannan yanayin, nazarin da ke kwatanta daidaito da inganci ta hanyar amfani da hanyoyin gargajiya, ana buƙatar ƙirar DM, da ƙirar koyo mai zurfi akan samfurori iri ɗaya don tabbatar da ko basirar wucin gadi na iya shawo kan waɗannan bambance-bambancen launin fata a cikin iyakataccen shekaru.kimantawa.
Mun nuna cewa ana iya maye gurbin hanyoyin gargajiya ta hanyar ƙididdige shekaru dangane da ƙirar DM a cikin aikin ƙididdige shekarun bincike a Koriya.Mun kuma gano yuwuwar aiwatar da koyan na'ura don tantance shekarun bincike.Duk da haka, akwai ƙayyadaddun ƙayyadaddun ƙayyadaddun bayanai, kamar ƙarancin adadin mahalarta a cikin wannan binciken don ƙayyade ainihin sakamakon, da kuma rashin binciken da aka yi a baya don kwatanta da tabbatar da sakamakon wannan binciken.A nan gaba, ya kamata a gudanar da nazarin DM tare da adadi mai yawa na samfurori da kuma yawan jama'a daban-daban don inganta aikin da ya dace idan aka kwatanta da hanyoyin gargajiya.Don tabbatar da yuwuwar yin amfani da hankali na wucin gadi don ƙididdige shekaru a cikin yawan jama'a da yawa, ana buƙatar karatun gaba don kwatanta daidaiton rarrabawa da ingancin DM da ƙirar koyo mai zurfi tare da hanyoyin gargajiya a cikin samfuran iri ɗaya.
Binciken ya yi amfani da hotuna 2,657 na bango da aka tattara daga manyan Koriya da Japan masu shekaru 15 zuwa 23.An raba radiyon rediyo na Koriya zuwa tsarin horo na 900 (shekaru 19.42 ± 2.65) da 900 na gwajin ciki (19.52 ± 2.59 shekaru).An tattara tsarin horon a wata cibiya (Asibitin Seoul St. Mary's), kuma an tattara nasu gwajin a cibiyoyi biyu (Asibitin Dental na Jami'ar Seoul da Asibitin Hakora na Jami'ar Yonsei).Mun kuma tattara radiyo 857 daga wani bayanan tushen yawan jama'a (Jami'ar Kiwon Lafiya ta Iwate, Japan) don gwaji na waje.An zaɓi radiyo na batutuwan Jafananci (19.31 ± 2.60 shekaru) azaman saitin gwajin waje.An tattara bayanai a baya-bayan nan don nazarin matakan haɓaka haƙori akan faifan rediyo na panoramic da aka ɗauka yayin jiyya na haƙori.Duk bayanan da aka tattara ba a san su ba sai ga jinsi, ranar haihuwa da ranar rediyo.Ƙididdigar haɗawa da ƙaddamarwa sun kasance daidai da binciken da aka buga a baya 4, 5.An ƙididdige ainihin shekarun samfurin ta hanyar rage ranar haihuwa daga ranar da aka ɗauki hoton rediyo.An raba rukunin samfurin zuwa ƙungiyoyin shekaru tara.An nuna shekarun da rabon jima'i a cikin Tebur na 3 An gudanar da wannan binciken bisa ga sanarwar Helsinki kuma an amince da Hukumar Kula da Harkokin Kasuwanci (IRB) na Seoul St. Mary's Hospital na Jami'ar Katolika na Koriya (KC22WISI0328).Sakamakon sake fasalin wannan binciken, ba za a iya samun izini da aka sani ba daga duk majinyata da ke yin gwajin rediyo don dalilai na warkewa.Asibitin St. Mary's na Jami'ar Seoul (IRB) ya yi watsi da buƙatun don yarda da sanarwa.
An tantance matakan haɓakawa na molars na biyu da na uku bisa ga ka'idojin Demircan25.Haƙori ɗaya ne kawai aka zaɓa idan an sami nau'in haƙori iri ɗaya a gefen hagu da dama na kowane muƙamuƙi.Idan hakora masu kama da juna a bangarorin biyu sun kasance a matakai daban-daban na ci gaba, an zaɓi haƙoran da ke da ƙananan haɓaka don yin la'akari da rashin tabbas a cikin shekarun da aka kiyasta.Hotunan radiyo guda ɗari da bazuwar da aka zaɓa daga saitin horon kwararru biyu ne suka zira kwallaye don gwada amincin interobserver bayan tantancewa don tantance matakin balaga hakori.An tantance amincin intraobserver sau biyu a tsakar watanni uku ta mai lura na farko.
Matsayin jima'i da ci gaba na molars na biyu da na uku na kowane muƙamuƙi a cikin tsarin horo an ƙididdige su ta hanyar mai lura da farko da aka horar da nau'ikan DM daban-daban, kuma an saita ainihin shekarun a matsayin ƙimar manufa.Samfurin SLP da MLP, waɗanda aka yi amfani da su sosai a cikin koyan na'ura, an gwada su da algorithms na koma baya.Samfurin DM ya haɗa ayyukan layi ta amfani da matakan haɓaka na hakora huɗu kuma ya haɗa waɗannan bayanai don kimanta shekaru.SLP ita ce hanyar sadarwa mafi sauƙi kuma baya ƙunshi ɓoyayyun yadudduka.SLP yana aiki akan watsa kofa tsakanin nodes.Samfurin SLP a cikin koma baya yana da kamanceceniya da lissafi da koma baya na layi daya.Ba kamar ƙirar SLP ba, ƙirar MLP tana da ɓoyayyun yadudduka da yawa tare da ayyukan kunnawa marasa kan layi.Gwaje-gwajenmu sun yi amfani da ɓoye mai ɓoye tare da ɓoyayyun nodes 20 kawai tare da ayyukan kunnawa marasa kan layi.Yi amfani da zuriyar gradient azaman hanyar ingantawa da MAE da RMSE azaman aikin asara don horar da ƙirar koyon injin mu.An yi amfani da mafi kyawun samfurin regression da aka samu a cikin gwaje-gwaje na ciki da na waje kuma an kiyasta shekarun hakora.
An ƙirƙiri algorithm rarrabuwa wanda ke amfani da balagaggu na hakora huɗu akan tsarin horo don hasashen ko samfurin yana da shekaru 18 ko a'a.Don gina samfurin, mun samo na'ura mai wakiltar bakwai algorithms na koyo 6,43: (1) LR, (2) KNN, (3) SVM, (4) DT, (5) RF, (6) XGBoost, da (7) MLP .LR shine ɗayan mafi yawan amfani da algorithms rarrabuwa44.Algorithm na ilmantarwa ne da ake kulawa wanda ke amfani da koma baya don hasashen yuwuwar bayanan mallakar wani nau'i daga 0 zuwa 1 kuma yana rarraba bayanan a matsayin na wani nau'i mai yuwuwa dangane da wannan yuwuwar;akasari ana amfani da shi don rarraba binary.KNN yana ɗaya daga cikin mafi sauƙi algorithms koyon inji45.Lokacin da aka ba da sabon bayanan shigarwa, ta nemo bayanan k kusa da saitin da ke akwai sannan ya rarraba su cikin ajin tare da mafi girman mitar.Mun saita 3 don adadin maƙwabta da aka yi la'akari (k).SVM algorithm ne wanda ke haɓaka tazara tsakanin azuzuwan biyu ta amfani da aikin kernel don faɗaɗa sararin layi zuwa sarari mara layi wanda ake kira filayen46.Don wannan ƙirar, muna amfani da son rai = 1, iko = 1, da gamma = 1 a matsayin hyperparameters don kwaya mai yawa.An yi amfani da DT a fagage daban-daban azaman algorithm don rarraba duk bayanan da aka saita zuwa ƙungiyoyi da yawa ta hanyar wakiltar ƙa'idodin yanke shawara a cikin tsarin itace47.An saita samfurin tare da ƙaramin adadin rikodin kowane kumburi na 2 kuma yana amfani da ma'aunin Gini a matsayin ma'aunin inganci.RF wata hanya ce ta dunƙulewa wacce ke haɗa DTs da yawa don haɓaka aiki ta amfani da hanyar tattara bootstrap wanda ke haifar da rarrauna mai rarrabawa ga kowane samfurin ta hanyar zana samfuran girman girman sau da yawa daga asali dataset48.Mun yi amfani da bishiyu 100, zurfin bishiyar 10, mafi ƙarancin girman kumburi 1, da ma'aunin gini admixture a matsayin ma'aunin rabuwar kumburi.An ƙayyade rarrabuwar sabbin bayanai ta hanyar kuri'a mafi rinjaye.XGBoost algorithm ne wanda ke haɗa dabarun haɓakawa ta amfani da hanyar da ke ɗaukar bayanan horon kuskure tsakanin ainihin ƙimar ƙirar da ta gabata da haɓaka kuskure ta amfani da gradients49.Algorithm ɗin da aka yi amfani da shi sosai saboda kyakkyawan aikin sa da ingantaccen kayan aiki, da kuma babban abin dogaro a matsayin aikin gyaran da ya wuce kima.Samfurin yana sanye da ƙafafun tallafi 400.MLP wata hanyar sadarwa ce ta jijiya wacce ɗaya ko fiye da na perceptrons ke samar da yadudduka da yawa tare da ɓoyayyun yadudduka ɗaya ko fiye tsakanin shigarwa da matakan fitarwa38.Yin amfani da wannan, zaku iya aiwatar da rarrabuwa mara layi inda lokacin da kuka ƙara ƙirar shigarwa kuma sami ƙimar sakamako, ƙimar sakamakon da aka annabta ana kwatanta shi da ainihin ƙimar sakamako kuma ana yada kuskuren baya.Mun ƙirƙiri wani ɓoye mai ɓoye tare da ɓoyayyun neurons guda 20 a cikin kowane Layer.Kowane samfurin da muka haɓaka an yi amfani da shi zuwa saiti na ciki da na waje don gwada aikin rarrabuwa ta hanyar ƙididdige hankali, ƙayyadaddun bayanai, PPV, NPV, da AUROC.An bayyana azanci a matsayin rabon samfurin da aka kiyasta ya kai shekaru 18 ko sama da haka zuwa samfurin da aka kiyasta ya kai shekaru 18 ko sama da haka.Ƙayyadaddun ƙayyadaddun samfuran da ke ƙasa da shekaru 18 da waɗanda aka kiyasta su kasance ƙasa da shekaru 18.
Matakan hakori da aka tantance a cikin tsarin horo an canza su zuwa matakan ƙididdiga don ƙididdigar ƙididdiga.An yi gyare-gyaren layi mai yawa da kuma kayan aiki don haɓaka ƙirar tsinkaya ga kowane jima'i da kuma samo hanyoyin da za a iya amfani da su don kimanta shekaru.Mun yi amfani da waɗannan dabarun don ƙididdige shekarun haƙori don tsarin gwaji na ciki da na waje.Tebur na 4 yana nuna koma baya da ƙirar ƙira da aka yi amfani da su a cikin wannan binciken.
An ƙididdige amincin intra- da interobserver ta amfani da kididdigar kappa na Cohen.Don gwada daidaito na DM da na al'ada regression model, mun lissafta MAE da RMSE ta yin amfani da ƙididdiga da kuma ainihin shekaru na ciki da na waje gwaje-gwaje.Ana amfani da waɗannan kurakurai akai-akai don kimanta daidaiton tsinkayar ƙira.Karamin kuskuren, mafi girman daidaiton hasashen24.Kwatanta MAE da RMSE na saitin gwajin ciki da na waje da aka ƙididdige su ta amfani da DM da koma bayan al'ada.An tantance aikin rarrabuwa na yankewar shekaru 18 a cikin ƙididdiga na al'ada ta amfani da tebur na gaggawa na 2 × 2.Ƙididdigar ƙididdiga, ƙayyadaddun ƙayyadaddun bayanai, PPV, NPV, da AUROC na saitin gwajin an kwatanta su tare da ma'auni na ƙirar ƙirar DM.Ana bayyana bayanai azaman ma'anar ± daidaitaccen karkacewa ko lamba (%) dangane da halayen bayanai.Ƙimar P mai gefe biyu <0.05 an yi la'akari da mahimmancin ƙididdiga.An yi duk ƙididdigar ƙididdiga ta yau da kullun ta amfani da sigar SAS 9.4 (Cibiyar SAS, Cary, NC).An aiwatar da ƙirar DM regression a cikin Python ta amfani da Keras50 2.2.4 backend da Tensorflow51 1.8.0 musamman don ayyukan lissafi.An aiwatar da samfurin rarrabawa na DM a cikin muhallin Binciken Ilimi na Waikato da kuma Konstanz Information Miner (KNIME) 4.6.152 dandalin bincike.
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