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Hakora ana daukar su ne mafi girman mai nuna girman kai na jikin mutum kuma galibi ana amfani dasu cikin kimantawa na zamani. Mun yi niyyar inganta kimanta tsarin ma'adinai mai guba ta hanyar kwatanta ƙimar daidaitawa da kuma ayyukan gargajiya na ƙauyukan shekaru 18 tare da ƙimar gargajiya da kimantawa na zamani. An tattara adadin hotunan 2657 daga Koriya da Jafananci shekaru 15 zuwa 23. An kasu kashi biyu na horo, kowannensu yana dauke da rediyo na Koriya 900, da kuma gwajin gwaji na ciki wanda ya ƙunshi hotunan rediyo 857. Mun gwada daidaitaccen daidaitawa da ingancin hanyoyin gargajiya tare da tsarin gwajin ma'adinai. Daidaitaccen tsarin gargajiya akan saitin gwajin na ciki ya dan kadan sama da na samfurin ma'adinai, kuma bambanci yana da karami <0.24 cikakken kuskure ne <0.24 Shekaru). Ayyukan rarrabuwa na wasan kwaikwayo na shekaru 18 na yanke kama tsakanin hanyoyin gargajiya da samfuran ma'adinai. Don haka, za a iya maye gurbin hanyoyin ma'adanan bayanai yayin aiwatar da kimantawa na zamani ta amfani da balaga na biyu da kuma matasa matasa da matasa matasa.
Ana amfani da kimantawa da yawan hakori da yawa a cikin magungunan liyafa da ilimin likitancin da aka yi. Musamman, saboda babban haɗin kai tsakanin kimanin tarihin shekara da mahimmancin yanayin ci gaba na ilimin haƙori da matasa ne mai muhimmanci ga kimanta shekaru da yara da matasa1,2,3. Koyaya, ga matasa, kimanta haƙori shekaru bisa ga ilimin hakori yana da iyakance saboda hakane hakane ya kusan gama, ban da na uku morants. Dalilin tantance talakawa da matasa shine samar da ingantaccen kiyasta da shaidar kimiyya na ko sun kai ga mafi yawan mutane. A cikin ayyukan koyarwar 'yan kasuwa da matasa a cikin Koriya, Age an kiyasta ta amfani da hanyar Lee, kuma an yi hasashen cewa bakin doka da aka ruwaito shi bisa bayanan Oh et al 5.
Ilimin injin wani nau'in ilimin wucin gadi ne (AI) wanda ya saba koyo da kuma rarrabe bayanai da yawa, da kuma yin shirye-shirye na bayanan. Ilimin injin na iya gano amfani ɓoye ɓoyayyen alamu a cikin manyan bayanan bayanai. Sabanin haka, hanyoyin gargajiya, waɗanda ke da aiki-aiki-m da cin abinci mai lokaci, na iya samun iyakoki yayin ma'amala da manyan kundin bayanan hadaddun data waɗanda suke da wuya a aiwatar da hannu da hannu 7. Saboda haka, an gudanar da karatun da yawa kwanan nan ta amfani da sabbin fasahohin kwamfuta don ragewar kurakurai da rage yawan bayanai ,,9,10,11,11. Musamman, an yi amfani da koyo mai zurfi a cikin binciken hoto na likita, da hanyoyi daban-daban na kimantawa ta atomatik an yi shi don inganta daidaito da ingancin shekaru 43,16,19,19,19,19,19 . Misali, Halabi et Al 13 ya kirkiro da injin din da aka samu algorithm ya samo asali ne daga hanyoyin da ke dauke da kai mai yanke shawara ta amfani da zumunta na hannun yara. Wannan binciken yana ba da samfurin wanda ya shafi injin koyon likita kuma yana nuna cewa waɗannan hanyoyin na iya haɓaka daidaito na bincike. Liet al14 An kiyasta shekaru daga hotunan pelvic ta amfani da mai korar CNN kuma idan aka kwatanta su da sakamakon tashin hankali na amfani da cigaba. Sun gano cewa zurfin koyon CNN samfurin ya nuna yawan kimantawa iri ɗaya kamar tsarin gargajiya na gargajiya. Guo et al. Nazari [15] Aiwatar da yanayin da ake yi na CNN Fasaha, da sakamakon samfurin CNN na CNN, kuma sakamakon samfurin CNN na CNN, da kuma sakamakon samfurin CNN na CNN, kuma sakamakon samfurin CNN na CNN, da kuma sakamakon samfurin CNN na CNN.
Most studies on age estimation using machine learning use deep learning methods13,14,15,16,17,18,19,20. Asididdige shekaru dangane da zurfin koyo an ruwaito shine mafi daidai da hanyoyin gargajiya. Koyaya, wannan hanyar tana samar da karamin damar da za ta gabatar da ilimin kimiyyar kimiya na zamani, kamar alamun shekarun da ake amfani da su a kimatun. Akwai kuma tsarin doka akan wanda ke gudanar da binciken. Sabili da haka, kimantawa shekaru bisa ga zurfin koyo yana da wuya a yarda da hukumomin gudanarwa da shari'a. Mining din (DM) dabara ce da za ta iya gano ba kawai tsammani ba amma kuma ba da bayani ba a tsammani a matsayin hanya don gano daidaitattun bayanai tsakanin data Litattafai6,21,22. Ana amfani da koyo na injin a cikin ma'adinai na bayanai, da kuma ma'adinai na bayanan amfani da amfani da algorithms guda ɗaya don gano tsarin a cikin bayanai. Asididdigar shekaru ta amfani da ci gaban hakori ya samo asali ne daga kimanta mai balaguron hakora, kuma wannan kimantawa ya bayyana a matsayin mataki na kowane haƙora. Za'a iya amfani da DM don bincika gyaran tsakanin matakin ilimin haƙori da zamanin da kuma yana da yuwuwar maye gurbin ƙididdigar ƙididdiga na gargajiya. Sabili da haka, idan muna amfani da dabarun DM don kimantawa, za mu iya aiwatar da koyan injin da yawa na kimantawa game da abin alhakin doka. An buga karatun digiri da yawa a kan hanyoyin da zasu iya yiwuwa ga hanyoyin gargajiya na yau da kullun da aka yi amfani da su a cikin aikin gungume da na asali don tantance disal tsufa. Shen et al23 ya nuna cewa samfurin DM ya fi daidai da tsarin gargajiya na gargajiya. Et al24 amfani da hanyoyi daban-daban na DM sun yi amfani da shekaru daban-daban saboda hanyoyin da DM ya nuna cewa hanyar DM ta ƙididdige yawan yawan jama'ar Faransawa.
Domin kimanta hakori da tsufa na Korean da matasa, manya 4 an yi amfani da ita a cikin aikin Koriya na Koriya. Wannan hanyar tana amfani da bincike na gargajiya (kamar sasantawa da yawa) don bincika dangantakar da ke tsakanin Koriya da tsufa na zamani. A cikin wannan binciken, ana iya kimanta hanyoyin zamani da aka samu amfani da hanyoyin ƙididdigar ƙididdigar al'ada ana bayyana su azaman "hanyoyin gargajiya." Hanyar Lee ita ce hanya ce ta al'ada, kuma OH ET AL. 5; Koyaya, amfani da kimantawa na zamani dangane da samfurin DM a cikin aikin Koriya na Koriya har yanzu yana da tambaya. Manufarmu ita ce a kimanta amfani da amfanin ƙarnin zamani dangane da samfurin DM. Dalilin wannan binciken ya (1) don kwatanta daidaitaccen samfuran DM guda biyu a kimanta aikin Dem na 7 na DM yana da shekaru 18 tare da waɗanda aka samu Amfani da Matsayin Magungunan gargajiya na na biyu da na uku moral a cikin duka muƙubs.
Yana nufin da daidaitaccen karkacewa na shekaru na shekara-shekara da mataki da nau'in haƙori S2 (gwajin horo na ciki), da ƙarin tebur na gwaji). Kamfanin KAPPA don tawakkali na ciki- da kuma dogaro da hankali da aka samu daga tsarin horo sun kasance 0.951 da 0.947, bi da bi. P dabi'u da kashi 95% na kwarin gwiwa don ƙimar Kappa ana nuna su a cikin Table ƙarin Teburin Kan S4. An fassara darajar kappa a matsayin "kusan cikakke", m tare da ka'idodin Landis da koch26.
Lokacin da aka kwatanta ma'anar kuskure (Mae), hanyar gargajiya ta daina yin samfurin DM ga dukkan mahalukan kuma a cikin gwajin maza da aka saita, in banda gwajin Multile Pervopron (MLP). Bambanci tsakanin tsarin gargajiya da samfurin DM akan gwajin gwajin na ciki shine 0.12-0.19 shekaru don maza da 0.17-0 biliyan mata. Don baturin gwajin waje, bambance-bambance suna da karami (0.001-0.05 shekaru ga maza da 0.onyina 20-0.09 shekaru ga mata). Bugu da ƙari, tushen ma'anar kuskure. ). MLP ya nuna dan kadan kyau fiye da Super Layer Etpopron (SLP), ban da batun saitin gwajin mace na waje. Don Mae da RMSE, gwajin gwajin waje ya fi girma fiye da tsarin gwajin na ciki don dukkanin halittun da samfura. Duk Mae da RMSE ana nuna su a Table 1 da Hoto 1.
Mae da RMSE na gargajiya da bayanan masu hawan harkokin gyara. Ma'anar cikakken kuskure Mae, kuskuren ma'anar murabba'i Rmse, Single Layer Enpotron Slp, Wurin Mulliforet MLP, hanyar Comm.
An nuna wasan kwaikwayon (tare da Cutoff na shekaru 18) na gargajiya na gargajiya da DM an nuna shi dangane da hankali, takamaiman darajar (NPV), da yanki mai mahimmanci a ƙarƙashin ƙimar mai karɓa (Auroc) 27 (Tebur 2, Hoto na 2 da karin bayani 1 kan layi). A cikin sharuddan sha'awar batir na gwajin ciki, hanyoyin gargajiya suna da kyau a tsakanin mutane da muni a cikin mata. Koyaya, bambanci a cikin aikin rarrabuwa tsakanin hanyoyin gargajiya da SD shine 9.7% ga maza (MLP) kuma 2.4% na mata (XGboost). Daga cikin ƙirar DM, tashin hankali mai rikitarwa (LR) ya nuna mafi kyawun abin mamaki a cikin mata biyu. Game da takamaiman gwajin gwajin, an lura cewa samfuran SD hudu ne, yayin da samfurin gargajiya ya yi kyau a mata. Bambanci a wasan rarrabuwa ga maza da mata sune kashi 13.3% (MLP), bi da bi da su (MLP), da nuna cewa banbanci na rarrabuwa tsakanin ƙayyadadden samfuran ya wuce abin da ya wuce. Daga cikin ƙirar DM, injin ɗin da aka tallafawa (SVM), itacen yanke shawara (DT), da kuma bazuwar daji (yayin da aka yi amfani da ƙaddarar daji a cikin maza, yayin da samfurin da aka yi a cikin maza. Auroc na samfurin gargajiya da duk samfuran SD sun fi 0.925 (K-Baborori (Knn) a cikin maza), na nuna kyakkyawan rarrabuwa a cikin warassi na shekaru 188. Don gwajin waje, akwai raguwar a cikin aikin rarrabuwa cikin yanayin fahimta, takamaiman da kuma Auroc idan aka kwatanta da gwajin gwajin ciki. Haka kuma, bambanci cikin hankali game da takamaiman samfuran gama-gari da mafi munin ƙirar da aka fi dacewa da bambanci a cikin gwajin gwajin ciki.
Hankali da kuma ingancin bayanan tsarin ma'adinai idan aka kwatanta da hanyoyin gargajiya tare da cutarwa na shekaru 18. Knn K nearest maƙwabta, TVM Tallafawa Mashin Vector, lr Logistic Brough, DEp Det, Defen yanke shawara, Kompultiost Perfevort, MLP Mulllah Perpoptron, MLP Way.
Mataki na farko a cikin wannan binciken shine kwatancin daidaito na kimantawa na hakane da aka samu daga samfuran DM bakwai tare da waɗanda aka samu ta amfani da rikicin gargajiya. Mae da Rmse an kimanta su a gwajin gwajin ciki don mata da maza, da bambanci tsakanin hanyar gargajiya da kuma samfurin DM zuwa 77 zuwa 77 zuwa 78 kwanaki don RMSE. Kodayake hanyar al'ada ta kasance mafi daidaituwa a cikin wannan binciken, yana da wuya a yanke ko irin wannan karamin bambanci yana da mahimmanci ko mahimmanci. Wadannan sakamakon suna nuna cewa daidaito na kimantawa na menal yana amfani da ƙirar DM kusan ɗaya ce ta hanyar al'ada. Kai tsaye kwatankwacin sakamako daga karatun da suka gabata yana da wahala saboda babu wani nazari ya kwatanta daidaitattun ƙirar DM tare da hanyoyin ƙididdigar al'ada ta amfani da dabarun rikodin guda ɗaya a cikin wannan binciken. Et Al24 ya kwatanta Mashin da RMSe tsakanin hanyoyi biyu na gargajiya (Demirjian Hanyar29) da kuma Willems Hanyar 29) da samfurori 10 na DM a cikin shekaru 2 zuwa 24 shekaru. Sun bayar da rahoton cewa duk samfuran DM sun kasance sun yi daidai fiye da hanyoyin gargajiya, tare da bambance-bambance na 0..25 da 0.47 shekaru a cikin RMSEL da hanyoyin RMSEMS, bi da bi da bi. Bambancin tsakanin samfurin SD da hanyoyin gargajiya da aka nuna a binciken Halibourg suna la'akari da rahotanni da yawa a cikin yawan mutanen da ke cikin wannan binciken da na binciken ya samo asali. A cikin wannan binciken. Taif et al 34 ya yi amfani da MLP Algorithm don hango masu haƙƙin haƙora daga 1636 Sinawa na kasar Sin kuma idan aka kwatanta daidaitawar da ta lalata da willems. Sun bayar da rahoton cewa MLP yana da daidaito fiye da hanyoyin gargajiya. Bambanci tsakanin hanyar kwayar halitta kuma hanyar gargajiya ita ce <0.32, kuma hanyar willems ita ce shekaru 0.2.28, wanda yayi kama da sakamakon binciken yanzu. Sakamakon waɗannan binciken da ya gabata24,34 ma sun yi daidai da sakamakon binciken yanzu, da kuma kimantawa kimanin ƙirar DM kuma hanyar gargajiya ta yi kama da. Koyaya, dangane da sakamakon da aka gabatar, zamu iya tsananta ne kawai da amfani da ƙirar DM don kimanta shekaru na iya maye gurbin yanayin da ake ciki saboda karancin karatun da suka gabata. Binciken bincike ta amfani da manyan samfurori ana buƙatar tabbatar da sakamakon da aka samu a cikin wannan binciken.
Daga cikin karatun da ke gwada daidaito SD a kimanta daidai da shekaru, wasu sun nuna mafi girman daidaito fiye da karatunmu. Stepaniovsky et 39 SD ya shafi misalai 22 ga SD zuwa Panoramic Reliographs na 976 a mazauna mazauna shekaru 2.7 zuwa shekaru 20.5 kuma sun gwada daidaito kowane samfurin. Sun tantance ci gaban jimlar 16 da ƙananan haƙoran hagu na hagu ta amfani da ƙa'idojin rarrabuwa ta hanyar Mororrees et Al 36. Mae ya fito ne daga 0.64 zuwa 0.94 shekaru kuma RMSe ya kasance daga 0.85 zuwa shekaru 1.27 zuwa 1.27 shekaru da suka fi dacewa da samfurin DM guda biyu da aka yi amfani da su a wannan binciken. Shen et al23 ya yi amfani da hanyar da aka yi amfani da ita don kimanta haƙoran hakora bakwai na haƙora a cikin yankin da suka ragu a gabashin Sinawa da suka gabata kuma idan aka ƙididdige shi da shekaru 5 zuwa 13 da RF. Sun nuna cewa dukkan ƙirar DM guda uku suna da daidaito mai girma idan aka kwatanta da tsarin gargajiya na gargajiya. Mae da RMSE a cikin binciken Shen sun yi ƙasa da waɗanda ke cikin samfurin DM a wannan binciken. Yawan karuwar karatun ta Stepanovsky et al. 35 da kuma shen et al. 23 na iya zama saboda hada wasu 'yan darikan batutuwa a samfuran karatun su. Saboda kimanta shekaru don mahalarta tare da hakora masu tasowa sun zama cikakke kamar yadda yawan hakora zai iya lalata yadda mahalarta yawansu ke karami. Bugu da ƙari, kuskuren MLP a cikin kimantawa na zamani yana da ɗan ƙarami fiye da slp, ma'ana MLP ya fi daidai fiye da slp. Ana daukar MLP dan kadan mafi kyau ga kimantawa shekaru, mai yiwuwa saboda yadudduka masu ɓoyewa a cikin MLP38. Koyaya, akwai banbanci ga samfurin na waje na mata (SLP 1.45, MLP 1.49). Neman cewa MLP ya fi dacewa fiye da slp a cikin kimantawa shekaru yana buƙatar ƙarin karatun baya.
Aikin gargajiya na samfurin DM da kuma hanyar gargajiya a filin shekaru 18 kuma idan aka kwatanta. Dukkanin abubuwan da aka gwada SD da hanyoyin gargajiya akan gwajin da aka kafa na ciki da aka nuna kusan matakan nuna wariya ga mai shekaru 18 samfurin. Abin sani ga maza da mata sun fi ƙarfe 87.7% da 94.9%, bi da bi, da kuma takamaiman magana da 89.3%. Auroc na dukkan abubuwan da aka gwada su ma sun wuce 0.925. Zuwa mafi kyawun iliminmu, babu wani bincike da ya gwada wasan kwaikwayon na DM na dalilai na shekaru 18 dangane da balaga na hakori. Zamu iya kwatanta sakamakon wannan binciken tare da ayyukan rarrabuwa na samfuran koyo na samfuri akan kayan tarihi na panoramic. Guo et al.15 CIGABA DA GASKIYA DARI NA CIKIN CIKIN CIKIN CIKIN CNN-TARIHI DA AKE SAMUN LAFIYA DAGA CIKIN SAUKI NA DARAJI. Halin hankali da kuma ingancin hanyar jagora sun kasance 87.7% da 95.5%, da hankali, da kuma hakkin samfurin CNN ya wuce 89.2% da 86.6%, bi da bi 86.6%. Sun ƙarasa da cewa samfuran koyo masu zurfi na iya maye gurbin ko aiwatarwa na ƙididdigar ainihin abin da ke rarraba shekaru. Sakamakon wannan binciken ya nuna irin wannan batun. An yi imani da cewa rarrabuwa ta amfani da ƙirar DM na iya maye gurbin hanyoyin ƙididdiga na gargajiya saboda kimantawa shekaru. Daga cikin samfuran, DM LR shine mafi kyawun ƙimar hankali dangane da samfurin da na maza da hankali da kuma sani ga samfurin mace. LR ranks na biyu cikin salitta ga maza. Haka kuma, LR an dauke shi daya daga cikin samfuran DM35 masu amfani kuma ya kasance da wahala da wuya a aiwatar. Dangane da waɗannan sakamakon, LR an dauke shi mafi kyawun tsari na Cutoff na shekaru 18 da haihuwa a cikin Yawan Koriya.
Gabaɗaya, daidaitaccen kimantawa na zamani ko aikin rarrabuwa akan gwajin gwajin na waje ya kasance matalauta ko ƙarami idan aka kwatanta da sakamakon gwajin na ciki. Wasu rahotanni sun nuna cewa daidaitawar rarrabuwa ko ingantaccen aiki ya ragu yayin da ƙididdigar yawan Koriya ta dace da yawan mutanen Koriya. An kuma lura da wannan yanayin lalacewar a cikin samfurin DM. Saboda haka, don yin daidai kimantawa kimanta, koda lokacin amfani da DM a cikin bayanan na bincike, hanyoyin da aka samo daga bayanan asalin ƙasar, kamar yadda hanyoyin gargajiya, ya kamata a fi so su, ya kamata a fi so su .42,40,41. Tun da yake ba shi da tabbas ko samfuran koyo masu zurfi na iya nuna daidaito iri ɗaya, nazarin yana buƙatar ingantattun hanyoyin gargajiya na iya shawo kan samfuran gargajiya a ƙarancin shekaru. kimantawa.
Mun nuna cewa za a iya maye gurbin hanyoyin gargajiya ta hanyar kimar shekaru bisa tsarin karatun DM cikin kimantawa na zamani. Mun kuma gano yiwuwar aiwatar da koyan injiniyan kimar shekaru na zamani. Koyaya, akwai iyakance mafi ƙasƙanci, kamar karancin mahalarta taron a tabbacin ƙayyade sakamakon, da kuma rashin karatun da suka gabata don kwatantawa da tabbatar da sakamakon wannan binciken. A nan gaba, ya kamata a gudanar da karatun DM tare da yawancin samfurori masu girma tare da yawan jama'a don inganta aikinta na yau da kullun idan hanyoyin gargajiya. Don tabbatar da yiwuwa game da amfani da wucin gadi don ƙididdige shekaru a cikin yawan jama'a, ana buƙatar ƙirar koyon DM da ƙirar koyo tare da hanyoyin gargajiya a cikin samfurori iri ɗaya.
Nazarin da aka yi amfani da hotunan ortrographic 2,657 da aka tattara daga manya da Jafananci na Jafananci shekaru 15 zuwa 23. An kasuskara da Koriya cikin tsawan horo 900 (19.42 ± shekaru 2.65) da kuma kafa gwajin gwaji 900 (19.52 ± shekaru 2.59). An tattara horon a wani asibitin: Seoul St. Asibitin Mary V. Hakanan muna daukar rediyo 857 daga wasu bayanan wani yanki na yawan jama'a (IWEL UNCIONDI na likita, Japan) don gwajin waje. An zabi shekarun wasu batir (19.31 ± shekaru 2.60) a matsayin saitin gwajin waje. An tattara bayanai tun suna yin nazarin matakan ci gaba na hakori akan radiograogs na panalamic da aka ɗauka yayin maganin hakane. Duk bayanan da aka tattara sun kasance ba a san su ba sai dai da jinsi, ranar haihuwa da kwanan wata na radiograph. Haɗa da ƙa'idodi masu ƙididdiga sun kasance iri ɗaya kamar yadda aka buga karatun da aka buga a baya 4, 5. Ainihin shekaru na samfurin an lasafta ta rage ranar haihuwar daga ranar da rediyo aka dauka. An rarraba ƙungiyar samfurin zuwa ƙungiyoyi masu shekara tara. An nuna sauran shekaru da kuma rarraba jima'i a cikin Tebur 3 da aka gudanar ta hanyar sanarwar HelsinKi kuma an yarda da shi ta hanyar aikin nazarin Seoul St. Maryakin Maryamu (Iri2wisi0328). Saboda batun sake dawo da wannan binciken, ba za a iya samun yarda da yarda daga dukkan marasa lafiya ba wajen yin gwajin rediyo don dalilai na warkewa. Asibitin Jami'ar St. Maryamu (Iri) ta washe bukatar don izinin sanarwa.
Mataki na ci gaba na Bimaxillary na biyu da na uku Motsa aka kimanta bisa ga ka'idojin alamomin allo25. An zabi haƙori guda ɗaya kawai idan an samo irin wannan nau'in haƙori a gefen hagu da dama na kowane muƙamuƙi. Idan haƙoran hakora a bangarorin biyu sun kasance a matakai daban-daban, haƙoran da aka zaɓi ƙananan matakin ci gaba zuwa asusun da aka kiyasta a cikin shekaru da aka kiyasta. Guda biyu da aka zaba radiographs daga saitin horarwar da aka samu don gudanar da amincin tsaro guda biyu don gwada amincin da aka yiwa ta hanyar yanke hukunci a kan matakin balaga. An kula da amincin intraobserver sau biyu a cikin watanni uku ta hanyar mai lura da farko.
Jima'i da ci gaba na ci gaba na biyu da na uku suma na kowane mu'ujihu a cikin saiti na mai lura da shi, kuma an saita ainihin shekaru masu lura da manufa. SLP da MLP model, wanda aka yi amfani da shi sosai a cikin koyon injin, an gwada su da algorithms masu rikicewa. Model ɗin DM ya haɗu da ayyukan layi ta amfani da matakan haɓaka na Hakora huɗu kuma suna haɗu da waɗannan bayanan don ƙididdige shekaru. Slp shine mafi sauƙin cibiyar sadarwa da kuma ba ya ɗauke da ɓoye masu ɓoye. Slp yana aiki bisa ga yanayin watsa shirye-shirye tsakanin nodes. Tsarin SLP a cikin juyayi shine ilimin lissafi mai kama da rikice-rikice da yawa. Ba kamar samfurin SLP ba, samfurin MLP yana da yadudduka masu yawa tare da ayyukan sadarwar aikin. Gwajinmu ya yi amfani da ɓoye ɓoye tare da nodenes 20 kawai tare da ayyukan aikin ba da kyauta. Amfani da gradient lemun a matsayin hanyar ingantawa da Mae da Rmse a matsayin rmse a matsayin aikin asarar don horar da tsarin koyon injin mu. Mafi kyawun samfurin tashin hankali ya shafi saiti na ciki da na waje da kuma tsarin gwajin da aka kiyasta da kuma shekarun hakora.
An inganta Algorithm na rarrabuwa wanda yake amfani da balaga na hakora huɗu akan horon saita don yin hasashen ko samfurin yana da shekara 18 ko a'a. Don gina ƙirar, mun sami wakilcin injin bakwai da suka samo asali na algorithms6,43: (1) LR, (4) SVM, (7) RF, (7) DT, (7) dT, (7) . LR shine ɗayan mafi yawan amfani da rarrabuwa algorithms44. Kyakkyawan koyo na Algorithm mai mahimmanci wanda ke amfani da juyinya don hango ƙarfin data kasance a cikin wani rukuni na rukuni na yau da kullun dangane da wannan yiwuwa. galibi ana amfani da shi don rarrabuwa. KnN yana ɗaya daga cikin injin mai sauƙin koyo algorithms45. Lokacin da aka ba da sabon shigarwar bayanan shigarwar, ya sami data kusa da abubuwan da ake da gudana sannan kuma ya danganta su cikin aji tare da mafi girma mitar. Mun saita 3 don adadin maƙwabta da aka yi la'akari da su (k). SVM wani algorithm ne wanda ke daɗaɗa nesa tsakanin azuzuwan biyu ta amfani da aikin kernel don faɗaɗa sararin samaniya a cikin sararin samaniya da ake kira filaye46. Don wannan ƙirar, muna amfani da nuna bambanci = 1, wuta = 1, da gamma = 1 azaman hyperparsters don kwarkwalin polynomial. DT an yi amfani da shi a cikin filaye daban-daban a matsayin algorithm don rarraba duka bayanan da aka saita zuwa cikin ɗimbin zartarwa a cikin tsarin yanke na itace47. An daidaita samfurin tare da mafi ƙarancin adadin rikodin kowane kumburi na 2 kuma yana amfani da Gini ya zama mai inganci. RF yanki ne mai amfani wanda ya haɗu da Dubu da yawa don inganta aikin Taro na Taro na samfuran samfuri iri ɗaya daga cikin bayanan da yawa daga daidai. Mun yi amfani da bishiyoyi 100, zurfin itace 10, ƙimar node 1, da kuma Gini Vihirisa maniyayyen ra'ayi kamar yadda ƙayyadaddun rabuwa. An ƙayyade rarrabuwa Sabon bayanan da yawancin kuri'unsu. Xgboost wani algorithm ne wanda ke haɗu da dabarun haɓaka ta amfani da hanyar horar da ƙimar ƙimar da ta gabata da kuma haɓaka kuskuren ta amfani da gradients49. Algorithm da aka yi amfani da shi saboda kyakkyawan aiki da haɓaka albarkatunsa, har ma da babban abin dogaro a matsayin babban aikin gyara. Babban samfurin sanye da ƙafafun tallafi 400. MLP cibiyar sadarwa ne wanda ko fiye da Entspson form da yawa yadudduka tare da daya ko fiye da boyers yadudduka tsakanin shigar da fitarwa layers38. Yin amfani da wannan, zaku iya yin rarrabuwar kawuna wanda idan kun ƙara sakamakon sakamako, ƙimar sakamako mai mahimmanci ana buƙatar ƙimar sakamako na ainihi kuma an yada ƙimar sakamako da ainihin sakamako kuma an yada ƙimar sakamako. Mun kirkiro da ɓoye ɓoye tare da neurons 20 a cikin kowane Layer. Each model we developed was applied to internal and external sets to test classification performance by calculating sensitivity, specificity, PPV, NPV, and AUROC. An bayyana abin da aka sani a matsayin rabo na samfurin da aka kiyasta har shekara 18 ko fiye da wanda aka kiyasta cewa ya kasance shekaru 18 ko sama da haka. Halittu shine gwargwado na samfurori a cikin shekaru 18 kuma waɗanda aka kiyasta cewa suna cikin shekaru 18 da haihuwa.
Tsarin hakori da aka kiyasta a cikin horon saita an canza shi zuwa matakai na lambobi don bincike na ƙididdiga. Multivariate Linear da dabaru rikicewa an yi su don haɓaka ƙirar tsinkaya ga kowane irin jima'i da kuma samun dabarun da za a iya amfani da su don kimanta shekaru. Muna amfani da waɗannan dabarun don kimanta shekarun hakori don saiti na ciki da na waje. Tebur 4 yana nuna ƙirar ƙirar da aka yi amfani da shi a wannan binciken.
An yi lissafin dogaro da kai a ciki ta amfani da ƙididdigar Kifa ta Cohen. Don gwada daidaito na DM da kuma ƙirar gargajiya na gargajiya, mun lasafta MAE da RMSE ta amfani da kimantawa da kuma ainihin shekaru na gwaji na ciki da waje. Wadannan kurakuran ana amfani dasu don kimanta daidaito na tsinkaya. Karamin kuskuren, mafi girma daidaito na annabta24. Kwatanta Mae da RMSE na gwaji na ciki da waje wanda aka lissafta ta amfani da DM da rikicewar gargajiya. An tantance ayyukan digiri na Cutoff a cikin ƙididdigar na ɗan shekaru 18 ta amfani da teburin 2 × 2 teburin. Abinda aka lissafa da aka lissafa, Halitta, PPV, NPV, kuma auro na gwajin saitin da aka auna na samfurin DM. Ana bayyana bayanai kamar yadda ke nufin ± daidaitaccen daidaitawa ko lamba (%) dangane da halaye na bayanai. Halittar P dabi'u biyu <0.05 an ɗauke su ƙididdiga. Dukkanin binciken lissafi na yau da kullun an yi amfani da shi ta amfani da sigar SAS 9.4 (Cibiyar Sakawa, Cary, NC). An aiwatar da samfurin DM na DM a cikin Python ta amfani da Keras50 2.2.4 Balkend da Tensorflow51 1.8.0 musamman don ayyukan lissafi. An aiwatar da ƙirar DM a cikin ilimin Waiikato yanayin binciken da Minista na bayanan Konstanz (Knemi) 4,6.152.
The marubutan sun yarda cewa bayanan da ke goyon bayan shawarar binciken za a iya samu a cikin labarin da karin kayan. Bayanan bayanai da aka haifar da / ko nazarin yayin binciken suna daga marubucin mai dacewa akan buƙatun mai dacewa.
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