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F.S. Falcetta et al. General questions:

Artificial Intelligence In Medicine 137 (2023) 102487

4.6. Search term tests in all the databases and search strategy improvement s e a rWc he tienrimt i as l. l yWsee amr cahd ee ds et hv er or aulg chhaalnl gdeas t aa bn ads er es ,f i un teiml i zeinntgs ti nh et hper ospeoa sr ec hd tneurmmbs edr uor ifn ga r tt hi cilse sp rcoocnetses m, apilma tiendg at on di neclriema isne atthe e wsoe nr ks si t i uv intrye laant edd t ht oe tdhi see at os epsi .c , Tshui cs hp raos c ce lsisn iicma lp rtor ivael ss tohf e mi ne di tiicaal l sienatrecrhv efnotri oan sb froora dsepre cai nf idc complete search. 4.7. Database search s P e u a b r W M ch e ed d s , e a a t S a r c c b i h a e e s n d e c s e th u D e ti i l r s i e e z c l e e t d c , t f e S o d c r o d p th a u t i s a s , b w a a s n o e r d s k o Ww n e e N b re o : o v f C em o S c b c h i e r e r a n n 2 c e e n , . d I , T E 2 h E 0 e E 2 , 2 s A e . a C T r M h ch e , teearcmh s dwa tearbe a ss iemdi luaer bt ou t t ht he e dsief faerrcehn cset rs a ti en g yt h ne eleodgei dc a tl o o bp ee r da it fof resr eonft tfhoer sdeaatracbhasteooalrse. Tdheteasileeadrcihn tTearmblsesan2danthde 3n.umber of publications for each 4.8. Study selection b y FTSi Ft l easn adnFdKaAb. sWt r ae cstos lpvoe tde dn it si aa lgl ryeeelmi gei bn lt ei nwtehree isnc irtei ae nl seedl ei nc tdi eopnetnhdr eo nu tgl hy dr ei svci euws s i oann.d Tdhaet a f ue xl lt-rtaecxtti oenv awl uear et i ocno nfdour c tiendc l uf os iro nt h ei nf utlhl et esxytsst ei mn atthi ec soaf ma ue t mh oarns nwe ri t hb yt htehier saacmr oen yamu tsh ou rsse du si ni n gt hai s ssteacntdi oanr dai nz eddi nf oSr me c.t iTohnes 4l i.s9t and 4.10 is shown in Table 1. 4.9. Directions for quality evaluation of the selected studies i t gTi vhees q wu aeliigt yh te vt aol utahtei o inn if so ramn ai nt itoeng r ag la tphaer rt eodf. s yTsot e ams as et iscs r et hvei e ws esl es ci nt ecde ab ryt i cRl oe es ’h rqsu aelti t ya l .a n[ d4 2s]t.r eTnhget she, wq uee sutsi eo dn s t heev asleuta toef tqhuee spt iuornpso sper oopfo st he de rper soepaor scehd, ab racchkigt er oc tuunrde aa nn dd mc oent ht eoxdt o, l ol igt ey r, a rt ue sr ue l t rs e, vai enwd , t hr ee l arteel da t i wo no r ok f, tehc eu t ceodn bc lyu sFi oS Fn at on dt hFeKrAe s ienadr ce hp eonbdjeenc tt liyv.e sT. hQi su at ol ipt yi c eivs a al ul saot i ocno vwe raesd e ixn Section 5.10, and the quality evaluation questions are shown in Table 4. 4.10. Data extraction a m n e d n In t c s o t t m h h i p r s o l p e u t h g e a h d se d t , h is t e c w u d o s a s t a i a o u n t e h , x o a t r r n s a d c ( t F a io S t n F hi a t r a n d b d l a e F u s K t . h A W o ) r e r ( e s J a o C d l S v L e th ) d e h a e s l e l l p l t e e h c d e te s d d o i l s s v a t e u g d r d e i i e e s s - - cc ri fei pc aqnucei es ts i. oWn se fcoor nds tartuac et exdt r tawc toi osnt r. uDc at ut ar egdattahbelreesd wt hi t rho ug eg nhe trha il sa pn rdo scpe es s wasatshdeisccourseseindfobrymtahtrieoen aouf tthhoisrsre(FvSieFw, .FKA, and JCSL) and synthesized 5. Results a n dTahbes tsreaacrtcs hs cr rees eunl tiendg , i nw e1 9e9x 5c l ut idt leeds 1w8i 2t h5 1a 1r t3i c dl eusp, lai cnadt e5s5. Ienn tt ehree dt i ttlhe es fsut ul ld- ti ee xs tmeevtatl hu ea tiinocnl uf soiro ne l ci gr ii bt ei rl iitay. . WI ne tahded ef udl lt-wt eox tn ee wv a sl ut uadt iioens ns ot at gfeo,usni dx br eys uolut er ds eianr c8h s st ut rdaiteesg yw ai tsh r de faet rae nt oc ebse f reoxmt r aoctthe edr. aS rt tui dc li ee ss [t h4 3a t, 4d4e]a, lwt oh ni cl hy ww ii tt hh s2p6e escthu-dt oi e- ts e xi nt t tehcihs n coal ot eggyowr ye. r eWt eh ef opur inndc i ps iaxl rset ua sdoi ens f ocrl aesxs ci fliuesdi o ans, ss cy os tpeemraetvi ci erwe vs ,i eown.eWs teuedxyc lculda es sdi ftihe ed raesmcaoi nmi mn ge ns ttuadr yi e so rf olre ot ttehre, rarneda soonnes (cer ev aa tl iuoant i oonf os fu abct ictel epst afnocre tohf ec l hi neiacrai ln dg o icmu mp aeinr et adt,i ot ne xbt y- ovnol yi c ei ,n af ourtmo ma tai ot inc ehxatnrdaicctaiopns, and development of a program to help people with speech … ). Fig. 3 presents the flowchart and the result of the data extraction in Appendix, in Tables 6 and 7.

• Gs t Qr u1c:t uWr ehda ta ui nt ot eml lai gt iecn dt omc uo md eel ns t aa rt ieo nu soefd t ht oe scol ilnviec atlh he i sptroorbyl?e m o f • GdoQc2u:mWenhtaattiaorne? the challenges in creating automatic structured • GheQlp3:toWshoaltvep?roblems could structured automatic documentation • GmQe d4i:c aHl ocwa r ec oaunldd dsot rcut oc tru– pr eadt i eanutt oi nmt eartai cc t idooncsu?m e n t a t i o n i m p r o v e Specific questions: • Sa rQc1h:i t We c ht uarte aur see dt hteo sspoel vc ief i tch emsatcr hu icnt ue r el eda ranuitnogmma tei ct htor ad ns s ac rnidp t it ohne of the clinical history? • SteQrm2:s Hwohwenwtrearnesctrhiebinpgattihenetc’slinsyicmalphtoismtosrytr?anslated to medical • Si nQ 3p :u bHl iocwh ewaal tsh t shyes taepmpsl )i c, aatni odn wt he satte dw e( rl ae r gi tes- srceas luel t tse?s tWs assu ct hh e ar es arendiumcepdrodvoecmuemnetnitnatciaorne,ersruocrhs?as improved turnaround time and • SdQoc4t:orHsoawndwpaastiethnets?program acceptability by its users, such as • Sp Qu r5p: o sWe ?h aI st tahreer et haen yc od ma t ma eornc itahl e aupspe l iocfa tt ihoensse aa pv pa il li ac ba tl ieo nf os ?r t h i s 4.2. Designing a search strategy (search term generation) s e p n e o c T u i h g fi e h c , i q n s u o it e i s t a h t l i a o s t n e s a a . l r l c T h t h h e e te s r q c m u o e p s s e t w i o o e f n re s th w s e e e l s e r e e c a te r a c d d h d b r t e a e s s r s e m e d d s o n a n e n e d t d h e a e d ll g t t e o h n e e b r e s a t l u la d a r i n g e d e s cr eovniceewr n ionng at h ci so mt oppl ei ct e waenr de uf onuenddi t. e dS i nt rc ae n swc er i pht iaovne (ns ot rt i cfto cs up seeedc h t- ht oi s tinextet)ll,igtheencsee,aracnhd cnoanttuarianleldantegrumasgereplarotecdestsoinmg.achine learning, artificial 4se.s3s.mDenevt eclhoepcmkelinstt of a study selection criteria, procedure, and quality as p r i mI na rtyh isst updhiae ss e a, nwde c dr eeavteeldo ptehde tihn ec l us es iloe nc t iaonnd cer ixtcelrui as i ofno r c irdi teenr it ai f yai nn dg ae f fqeucat il vi teyl ya sps reos spmo seendt ca h ceoc mk l ipsut .t aWt i eo ni anlc lsuodl ue dt i oonn l tyo otrhi ge i npar lo ba lret imc l eos f t ht haet as iuotnoaml sa tai nc dd opcaut ime ne tnst.a Wt i oen eoxfc tl hu ed ei nd t ea rr at icctlieosn wb ietthw teheen fhoel al ol twh icnagr ec pr irtoe frei as -: sWc oe pues er edvai el lwt sh,ec po umbml i ce anttiaornys osre lleect tt ee rds ,i na nt hd es tt ri ti cl et ss apne de cahb- tsot r- taecxt tpsht ua sdei etso. find additional publications not found by the initial search strategy. 4.4. Creating a data extraction strategy iqnui et Wisat li e l o y n b . s a W s s e o e d t c t h r h a e e t at d e e a a d c ta h tw e o x o f tr t t a h a c e b t l i a e o u s n t c h o o o n n rs t t a h i i e n ni r n t e h g s i e s t a h r r e e c v h i g e e q w n u e e c r s a o ti l u o l a n d n s d f p il r l s o p i p n e o c s t if h e i d e c it ni of no r gmaat ht ieorne dd iirne ct thl iys epxhtar as ec t we da sf ruosme d t ht oe as ne lsewc et er dt haer tri ec lsee.a rTchhe qiunef os trimo nas proposed initially and is the main focus of this work. 4.5. Selection of databases (sources of information) t t h ec e h T n s h e o i a s lo rc g s h t y a . g a S e n i d n c c o h e n e s t a i h s lt t e h ed - s r u e i b l n a j t e s e c t d t ud t o y o f i p n t i h g cs is , an w r d e e v l i c i e s o w t n in te l g i m e d s p a l i t a n a t b e t d a h s e e a s i c n t o o t m er c p f o a r n e c h d e e u n o ct f - seinvgeinliesetroinf gD.atabases related to computer science, health, and software

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