March mein ek 63 saal ki khatoon routine checkup ke liye apne doctor ke paas jati hain. Blood test se pata chalta hai ke un ki sugar zyada reh rahi hai, aur unhein bataya jata hai ke unhein type 2 diabetes hai. Woh is ki ek aam dawai shuru karti hain aur unhein teen mahine baad dobara aane ko kaha jata hai.
June mein woh apne office ke qareeb ek lab se khoon ka test karwati hain, kyun ke ye clinic tak gaari chala kar jane se aasan hai. Un ki sugar March se zyada hai. Follow-up visit par nurse un ka wazan karti hai to pata chalta hai ke taqreeban nau pound kam hua hai, aur note mein likha jata hai ke woh lifestyle changes par achi tarah respond kar rahi hain. Woh aur un ke doctor dono khush hain.
August mein woh ek urgent care clinic jati hain, kamar ke beech mein dard ki shikayat le kar jo chand hafton se hai. Na woh giri hain, na koi bhaari cheez uthai hai. Unhein ek anti-inflammatory dawai di jati hai aur physical therapy ke liye refer kar diya jata hai.
Teeno doctors ne apne samne ka kaam kiya, aur har record alag se parha jaye to theek lagta hai. Saath parhein to ye ek aisi cheez ki taraf ishara karte hain jo koi akela nahi dikhata, aur jo doctor teeno dekhta, woh un ke pancreas ka scan karwana chahta.
Teeno visits ek doosre se kyun jurti hain
Pancreas ek chhota sa organ hai jo maide ke peeche gehrai mein, pet ki pichli deewar ke saath hota hai. Us ka ek kaam insulin banana hai, woh hormone jo blood sugar ko qaboo mein rakhta hai.
Yahi cheez teeno visits ko jorti hai. Pancreas mein tumor insulin banne ke amal ko bigar sakta hai, is liye blood sugar barh jati hai, kabhi kabhi kisi bhi aur nishani se pehle. Cancer se aisa wazan bhi kam ho sakta hai jis ki insaan ne koshish hi na ki ho. Aur kyun ke pancreas reerh ki haddi aur us ki nason ke qareeb hota hai, wahan ka tumor kamar ke beech mein halka halka dard paida kar sakta hai.
Nayi diabetes wale zyada tar logon ko cancer nahi hota. Lekin jab diabetes 50 saal ki umar ke baad pehli dafa saamne aaye, to taqreeban sau mein se ek ko teen saal ke andar pancreatic cancer diagnose hota hai, jo us umar mein mutawaqqa sharah se taqreeban aath guna hai. Mayo Clinic ke researchers ne aise mareezon ko dhoondne ke liye ek score banaya, jo is par mabni hai ke diabetes kis umar mein shuru hui, wazan kitna badla aur blood sugar kitni badli. Sugar barhte hue wazan ka girna sab se zyada wazan rakhta hai.
Waqt is liye ahem hai ke pancreatic cancer aam tor par der se pakra jata hai. Taqreeban aadhe cases tab diagnose hote hain jab cancer phail chuka hota hai, aur tab ilaaj bohat kam kar pata hai. Isay mahinon pehle pakar lena ye badal sakta hai ke kya kuch mumkin hai.
Is khatoon ke case mein zaroori maloomat pehle se record mein thi. Bas woh teen jagahon par bikhri hui thi, aur koi us sab ko ek saath nahi dekh raha tha.
Yahi khala ulti taraf bhi kaam karta hai. Maine aise mareez dekhe hain jin ki cardiac evaluations hoti rahin jab ke asal wajah anxiety thi aur dil ki be-tarteeb dharkan us ki ek alamat thi, aur aise mareezon ka ilaaj bhi kiya hai. Un ke dil ko poori ehtiyat se check kiya gaya, lekin jawab un ki kahani mein kahin aur tha. Jab kisi ki sehat ke tukre alag alag pare hon, to medicine sangeen baat miss kar deti hai aur ghair-zaroori cheezon ke peeche bhaagti hai.
Acha doctor pehle notice karta hai, phir amal se pehle evidence check karta hai. Medicine ke liye AI ko bhi isi tarah kaam karna chahiye.
Computers ne ye masla hal kyun nahi kiya
Computers insanon se kahin tez parhte hain, to ye poochna banta hai ke woh aise cases pehle se kyun nahi pakar lete. Wajah ye hai ke medicine mein zyada tar AI do mein se ek qism ki hai, aur har ek tasveer ka sirf ek hissa dekhti hai.
Pehli qism misaalon se seekhti hai. Laakhon purane mareezon ka data mile to woh seekh leti hai ke kaun se patterns aksar kisi bimari se pehle aate the. Bohat se log aaj jo chatbots use karte hain, woh isi tarah bane hain, text ki bohat bari miqdar par train ho kar. Is qism ki AI notice karne mein achi hai, lekin ye nahi dikha sakti ke kisi nateeje tak kyun pohanchi, aur ghalat hone par bhi utni hi pur-aitmaad lagti hai jitni sahi hone par. Doctor ek aise nateeje par mehfooz tareeqe se amal nahi kar sakti jise check karne ka us ke paas koi zariya na ho.
Doosri qism un rules par chalti hai jo logon ne likh kar rakhe hain, "agar ye, to woh" ki shakal mein. Rule saaf hota hai ke woh kya check karta hai aur kyun. Lekin woh sirf wahi pakarta hai jo kisi ne pehle se socha ho, aur sirf tab jab maloomat bilkul usi shakal mein aaye jis ki rule ko tawaqqo hai. Woh seekhta nahi.
Dono approaches adhoori hain, aur dono mein se koi bhi buri soch nahi.
Ek gehra masla un records mein hai jin se ye systems seekhte hain. Medical record ka bara hissa notes par mushtamil hai, aur har note ek insaan ka kisi visit ka bayan hai, jaldi mein likha hua aur is se mutasir ke us ne mareez ko kaise dekha. Baqi ka zyada tar hissa billing ke liye design hua tha, jahan diagnoses payment codes ki shakal mein store hoti hain. Jo system sirf is material se seekhta hai, woh is ke andhe kone bhi seekh leta hai. 2019 mein researchers ne paya ke American health systems mein extra care ke liye mareez chunne wala ek algorithm Black mareezon ko asal se zyada sehatmand samajh raha tha. Us ne purane kharche se seekha tha, aur un ki care par kam kharch kiya gaya tha.
Learning aur logic ek saath
Ache doctors dono tarah ki soch use karte hain. Saalon ki practice unhein sikhati hai ke kuch theek na ho to mehsoos kar lein, aur phir amal se pehle woh is tasur ko evidence par parakhte hain. Neuro-symbolic AI bhi isi tarah bani hai. "Neuro" wala hissa tajurbe ki tarah seekhta aur notice karta hai. "Symbolic" wala hissa rules ke saath sochta hai, jaise doctor evidence se milate waqt sochta hai.
Chroneme mein rules published research aur medical guidelines se aate hain, aur ek lens ki tarah kaam karte hain. Har clinical sawal ke liye ye tay karte hain ke kaun si maloomat ahem hai aur us ke source par kitna bharosa karna hai, taake scale par naapa gaya wazan note mein likhe kisi lafz se zyada wazan rakhe. Is daire ke andar learning wala hissa phir bhi aise patterns notice kar sakta hai jinhein likhne ka kisi ko khayal na aaya. Phir logic wala hissa har pattern ko evidence par parakhta hai, aur jo pattern is par poora na utre woh doctor tak recommendation ban kar kabhi nahi pohanchta.
Ab sochiye ke Chroneme isi khatoon ki care parh raha ho. Un ke lab results, wazan aur notes ek hi record mein aa jate hain, har us jagah se jahan woh gayin, usi tarteeb mein jis mein waqiaat hue. June mein jab un ki sugar barh rahi hai aur wazan gir raha hai, to ye pattern us cheez se mel khata hai jo published score dhoondta hai, aur un ke doctor ko ye finding usi hafte nazar aa jati hai, kamar dard shuru hone se do mahine pehle. Finding saada zabaan mein likhi hoti hai aur us ke peeche ka har result dikhati hai, har ek kahan aur kab record hua, aur woh study jis se rule liya gaya. Scan ka order pehle se tayyar hota hai, saath mein mareez ke liye ek message jo unhein ghabraye baghair wajah samjhata hai. Doctor isay dekhte hain, ittefaq ya ikhtilaf karte hain, aur sign karte hain.
Kyun ke rules likhe hue hain, is liye wahi facts har mareez ke liye wahi nateeja dete hain, chahe on call koi bhi ho. Jab evidence badalta hai, to rule ek dafa update hota hai aur sab par lagoo ho jata hai. Jab kuch ghalat ho, to pata lagaya ja sakta hai ke ghalti kahan hui.
Hum kya bana rahe hain
Behtar tareeqa akela kaafi nahi. Usay chalne ke liye ek system chahiye, aisa jo har insaan ka record mukammal rakhe aur das laakhwen mareez ke liye bhi utna hi acha kaam kare jitna pehle ke liye. Hum wahi system bana rahe hain.
Ye nayi qism ki baseerat ko bhi mumkin banata hai. Scan dikhata hai ke jism andar se kaisa hai, history dikhati hai ke woh wahan tak kaise pohancha, aur genetics dikhati hai ke us mein kis cheez ka imkaan zyada tha. Ye aam tor par alag alag, mukhtalif specialists parhte aaye hain. Ek saath aur tarteeb se parhe jayein to aise combinations samne aate hain jo kisi akele record mein nahi hote.
Medicine dahaiyon se janti hai ke achi, evidence-based care kaisi hoti hai. Jo kami rahi hai woh waqt ki hai, ke ye sara evidence har mareez par, har roz lagaya ja sake, kyun ke koi doctor har visit se pehle har record ko har guideline ke saath nahi mila sakta. Chroneme ke agents, yani aise programs jo kisi kaam ke qadam poore karte hain, ye tayyari karte hain. Woh orders, messages aur notes draft karte hain, har ek apne sources ke saath, taake clinician dekh kar sign kare. Judgment insanon ke paas rehti hai, aur bacha hua waqt care mein wapas jata hai.
Hum jo daawa karte hain us mein ehtiyat baratte hain. Ye ke har nateeje ka peecha kiya ja sakta hai aur usay check kiya ja sakta hai, aaj design ke lehaz se sach hai. System itni baar sahi hai ya nahi ke mareezon ki madad kare, ye evidence ka sawal hai. Hum isay ek aise protocol ke tehat test kar rahe hain jo koi bhi result dekhne se pehle likha gaya, aur jo kuch milega publish karenge, woh jagahen bhi jahan ye poora nahi utra.
Sources: 50 ke baad nayi diabetes aur pancreatic cancer: Chari et al., Gastroenterology, 2005. ENDPAC score: Sharma et al., Mayo Clinic, Gastroenterology, 2018. Diagnosis ke waqt stage: National Cancer Institute, SEER Cancer Stat Facts: Pancreatic Cancer (51% door tak phailne ke baad diagnose hue, 2016 se 2022). Care-management algorithm: Obermeyer et al., Science, 2019. Neuro-symbolic AI ki tafseel: Garcez aur Lamb, Artificial Intelligence Review, 2023.
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