Ishita Barua

• Olabintan, Olaolu; Halvorsen, Natalie Grace Mosteiro; Baddeley, Robin; Kudo, Shin Ei; Barua, Ishita & Misawa, Masashi [Show all 21 contributors for this article] (2025). Environmental impact of computer-aided diagnosis in colonoscopy: A carbon footprint assessment of a prospective study cohort. Endoscopy. ISSN 0013-726X. 58(03), p. 303–309. doi: 10.1055/a-2717-8365. Full text in Research Archive Show summary

  Background The environmental impact of computer-aided diagnosis (CADx) in colonoscopy is unknown. The potential to reduce greenhouse gas emissions by limiting unnecessary polypectomies may be offset by emissions associated with CADx devices. We quantified and compared the carbon footprint of colonoscopy with and without CADx. Methods Life-cycle carbon emissions associated with endoscopic snares, polyp traps, histopathology, and CADx devices were estimated using life-cycle assessment software. The effect of CADx was estimated by the carbon dioxide equivalent (CO2e) emissions related to outcomes from a prospective cohort of patients who underwent colonoscopy with optical diagnosis under a leave-in-situ strategy (i.e. rectosigmoid polyps ≤5 mm predicted as non-neoplastic were not removed) with and without CADx assistance. Results We analyzed 1134 individuals (median age 67 years, 59% male) with 1716 colorectal polyps. Colonoscopy with CADx reduced the number of snares and polyp traps from 567 to 543 (difference: 24) and histopathology submissions from 1343 to 1278 (difference: 65). However, the total carbon footprint increased from 832 kg CO2e (95%CI 815 to 847) without CADx to 946 kg CO2e (95%CI 927 to 965) with CADx, corresponding to an absolute increase of 114 kg CO2e (95%CI 80 to 150) or 0.10 kg CO2e per colonoscopy. Conclusion Using CADx under a leave-in-situ strategy increased the environmental burden of colonoscopy.

• Halvorsen, Natalie Grace Mosteiro; Barua, Ishita; Kudo, Shin-Ei; Gulati, Shraddha; Misawa, Masashi & Mori, Kensaku [Show all 19 contributors for this article] (2025). Leaving colorectal polyps in situ with endocytoscopy assisted by computer-aided diagnosis: a cost-effectiveness study. Endoscopy. ISSN 0013-726X. 57, p. 611–619. doi: 10.1055/a-2532-9282. Full text in Research Archive
• Jodal, Henriette C.; Wieszczy, Paulina; Klotz, Dagmar; Herfindal, Magnhild; Barua, Ishita & Tag, Petter [Show all 13 contributors for this article] (2023). A Comparison of Risk Classification Systems of Colorectal Adenomas: A Case-Cohort Study. Gastroenterology. ISSN 0016-5085. 165, p. 483–491. doi: 10.1053/j.gastro.2023.04.028. Full text in Research Archive Show summary

  Background & Aims Because post-polypectomy surveillance uses a growing proportion of colonoscopy capacity, more targeted surveillance is warranted. We therefore compared surveillance burden and cancer detection using 3 different adenoma classification systems. Methods In a case-cohort study among individuals who had adenomas removed between 1993 and 2007, we included 675 individuals with colorectal cancer (cases) diagnosed a median of 5.6 years after adenoma removal and 906 randomly selected individuals (subcohort). We compared colorectal cancer incidence among high- and low-risk individuals defined according to the traditional (high-risk: diameter ≥10 mm, high-grade dysplasia, villous growth pattern, or 3 or more adenomas), European Society of Gastrointestinal Endoscopy (ESGE) 2020 (high-risk: diameter ≥10 mm, high-grade dysplasia, or 5 or more adenomas), and novel (high-risk: diameter ≥20 mm or high-grade dysplasia) classification systems. For the different classification systems, we calculated the number of individuals recommended frequent surveillance colonoscopy and estimated number of delayed cancer diagnoses. Results Four hundred and thirty individuals with adenomas (52.7%) were high risk based on the traditional classification, 369 (45.2%) were high risk based on the ESGE 2020 classification, and 220 (27.0%) were high risk based on the novel classification. Using the traditional, ESGE 2020, and novel classifications, the colorectal cancer incidences per 100,000 person-years were 479, 552, and 690 among high-risk individuals, and 123, 124, and 179 among low-risk individuals, respectively. Compared with the traditional classification, the number of individuals who needed frequent surveillance was reduced by 13.9% and 44.2%, respectively, and 1 (3.4%) and 7 (24.1%) cancer diagnoses were delayed using the ESGE 2020 and novel classifications. Conclusions Using the ESGE 2020 and novel risk classifications will substantially reduce resources needed for colonoscopy surveillance after adenoma removal.

• Barua, Ishita; Misawa, Masashi; Brown, Jeremy R. Glissen; Walradt, Trent; Kudo, Shin-ei & Sheth, Sunil G. [Show all 19 contributors for this article] (2022). Speedometer for withdrawal time monitoring during colonoscopy: a clinical implementation trial. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2022.2154616. Full text in Research Archive
• Barua, Ishita; Wieszczy, Paulina; Kudo, Shin-ei; Masashi, Misawa; Holme, Øyvind & Gulati, Shraddha [Show all 34 contributors for this article] (2022). Real-Time Artificial Intelligence–Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy. NEJM Evidence. 1(6). doi: 10.1056/EVIDoa2200003. Full text in Research Archive
• Ainechi, Diba; Misawa, Masashi; Barua, Ishita; Larsen, Solveig; Paulsen, Vemund & Garborg, Kjetil Kjeldstad [Show all 21 contributors for this article] (2022). Impact of artificial intelligence on colorectal polyp detection for early-career endoscopists: an international comparative study. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. doi: 10.1080/00365521.2022.2070436. Full text in Research Archive Show summary

  Background Artificial intelligence (AI) for polyp detection is being introduced to colonoscopy, but there is uncertainty how this affects endoscopists’ ability to detect polyps and neoplasms. We performed a video-based study to address whether AI improved the endoscopists’ performance to detect polyps. Methods We established a dataset of 200 colonoscopy videos (length 5 s; 100 without polyps and 100 with one polyp). About 33 early-career endoscopists (50–400 colonoscopies performed) from 10 European countries classified each video as either ‘polyp present’ or ‘polyp not present’. The video assessment was performed twice with a four-week interval. The first assessment was performed without any AI tool, whereas the second was performed with an AI tool for polyp detection. The primary endpoint was early-career endoscopists’ sensitivity to detect polyps. Gold standard for presence and histology of polyps were confirmed by two expert endoscopists and pathologists, respectively. McNemar’s test was used for statistical significance. Results There were 86 neoplastic and 14 non-neoplastic polyps (mean size 5.6 mm) in the 100 videos with polyps. Early-career endoscopists’ sensitivity to detect polyps increased from 86.3% (95% confidence interval [CI]: 85.1–87.5%) to 91.7% (95%CI: 90.7–92.6%) with the AI aid (p < .0001). Their sensitivity to detect neoplastic polyps increased from 85.4% (95% CI: 84.0–86.7%) to 92.1% (95%CI: 91.1–93.1%) with the AI aid (p < .0001). Conclusion The polyp detection AI tool helped early-career endoscopists to increase their sensitivity to identify all polyps and neoplastic polyps during colonoscopy.

• Areia, Miguel; Mori, Yuichi; Correale, Loredana; Repici, Alessandro; Bretthauer, Michael & Sharma, Prateek [Show all 18 contributors for this article] (2022). Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study. The Lancet Digital Health. 4(6), p. e436–e444. doi: 10.1016/S2589-7500(22)00042-5. Full text in Research Archive Show summary

  Background Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools. Methods We conducted Markov model microsimulation of using colonoscopy with and without AI for colorectal cancer screening for individuals at average risk (no personal or family history of colorectal cancer, adenomas, inflammatory bowel disease, or hereditary colorectal cancer syndrome). We ran the microsimulation in a hypothetical cohort of 100 000 individuals in the USA aged 50–100 years. The primary analysis investigated screening colonoscopy with versus without AI every 10 years starting at age 50 years and finishing at age 80 years, with follow-up until age 100 years, assuming 60% screening population uptake. In secondary analyses, we modelled once-in-life screening colonoscopy at age 65 years in adults aged 50–79 years at average risk for colorectal cancer. Post-polypectomy surveillance followed the simplified current guideline. Costs of AI tools and cost for downstream treatment of screening detected disease were estimated with 3% annual discount rates. The main outcome measures included the incremental effect of AI-assisted colonoscopy versus standard (no-AI) colonoscopy on colorectal cancer incidence and mortality, and cost-effectiveness of screening projected for the average risk screening US population. Findings In the primary analyses, compared with no screening, the relative reduction of colorectal cancer incidence with screening colonoscopy without AI tools was 44·2% and with screening colonoscopy with AI tools was 48·9% (4·8% incremental gain). Compared with no screening, the relative reduction in colorectal cancer mortality with screening colonoscopy with no AI was 48·7% and with screening colonoscopy with AI was 52·3% (3·6% incremental gain). AI detection tools decreased the discounted costs per screened individual from $3400 to $3343 (a saving of $57 per individual). Results were similar in the secondary analyses modelling once-in-life colonoscopy. At the US population level, the implementation of AI detection during screening colonoscopy resulted in yearly additional prevention of 7194 colorectal cancer cases and 2089 related deaths, and a yearly saving of US$290 million. Interpretation Our findings suggest that implementation of AI detection tools in screening colonoscopy is a cost-saving strategy to further prevent colorectal cancer incidence and mortality. Funding European Commission and Japan Society of Promotion of Science.

• Barua, Ishita; Bretthauer, Michael & Mori, Yuichi (2022). Computer-aided quality assessment (CAQ): the next step for artificial intelligence in colonoscopy? Mini-invasive Surgery. 6. doi: 10.20517/2574-1225.2022.05. Full text in Research Archive
• Yu, Jingru; Refsum, Erle; Helsingen, Lise Mørkved; Folseraas, Trine; Ploner, Alexander & Wieszczy, Paulina [Show all 15 contributors for this article] (2022). Risk of hepato-pancreato-biliary cancer is increased by primary sclerosing cholangitis in patients with inflammatory bowel disease: A population-based cohort study. United European Gastroenterology Journal (UEG Journal). ISSN 2050-6406. 10(2), p. 212–224. doi: 10.1002/ueg2.12204. Full text in Research Archive Show summary

  Background There is continued uncertainty regarding the risks of hepato-pancreato-biliary cancers in patients with inflammatory bowel disease (IBD) with or without concomitant primary sclerosing cholangitis (PSC). Objective To give updated estimates on risk of hepato-pancreato-biliary cancers in patients with IBD, including pancreatic cancer, hepatocellular carcinoma, gall bladder cancer, and intra – and extrahepatic cholangiocarcinoma. Methods In a population-based cohort study, we included all patients diagnosed with IBD in Norway and Sweden from 1987 to 2016. The cohort comprised of 141,960 patients, identified through hospital databases and the National Patient Register. Participants were followed through linkage to national cancer, cause of death, and population registries. We calculated absolute risk and standardized incidence ratios (SIRs) of hepato-pancreato-biliary cancers by PSC and other clinical characteristics. Results Of the 141,960 IBD patients, 3.2% were diagnosed with PSC. During a median follow-up of 10.0 years, we identified 443 biliary tract cancers (SIR 5.2, 95% confidence interval [CI] 4.8–5.7), 161 hepatocellular carcinomas (SIR 2.4, 95% CI 2.0–2.7) and 282 pancreatic cancers (SIR 1.3, 95% CI 1.2–1.5). The relative risks were considerably higher in PSC-IBD patients, with SIR of 140 (95% CI 123–159) for biliary tract, 38.6 (95% CI 29.2–50.0) for hepatocellular, and 9.0 (95% CI 6.3–12.6) for pancreatic cancer. The SIRs were still slightly increased in non-PSC-IBD patients, compared to the general population. For biliary tract cancer, the cumulative probability at 25 years was 15.6% in PSC-IBD patients, and 0.4% in non-PSC-IBD patients. Conclusions The dramatically increased risks of hepato-pancreato-biliary cancers in PSC-IBD patients support periodic surveillance for these malignancies. While much lower, the excess relative risks in non-PSC-IBD patients were not trivial compared to non-IBD related risk factors.

• Jodal, Henriette C.; Juul, Frederik Emil; Barua, Ishita; Bretthauer, Michael; Kalager, Mette & Løberg, Magnus [Show all 7 contributors for this article] (2022). Emergency hospital admissions, prognosis, and population mortality in Norway during the first wave of the Covid-19 epidemic. Scandinavian Journal of Public Health. ISSN 1403-4948. 50(6), p. 795–802. doi: 10.1177/14034948221082959. Full text in Research Archive Show summary

  Background: During the first wave of the Covid-19 epidemic, a national lockdown was established in Norway, and inhabitants were asked to contact healthcare only if absolutely necessary. We investigated hospital admissions and mortality due to non-Covid-19 disease during the lockdown compared to previous years. Methods: We compared the number of emergency admissions and in-hospital fatality for diagnoses probably unaffected (acute myocardial infarction, acute abdominal conditions, cerebrovascular diseases) and affected by the lockdown (infections, injuries) in the South-Eastern Health Region of Norway during weeks 12–22, 2020, compared to the mean of the same period in the years 2017–2019. We also compared population mortality March–May 2020, to the mean of the same period in years 2017–2019. Results: A total of 280,043 emergency admissions were observed; 20,911 admissions probably unaffected, and 30,905 admissions probably affected by the lockdown. Admissions due to diagnoses probably unaffected was reduced by 12% (95% confidence interval (CI) 9–15%), compared to 2017–2019. Admissions for diagnoses probably affected was reduced by 30% (95% CI 28–32%). There was a 34% reduction in in-hospital fatality due to acute myocardial infarction (95% CI 4–56%), 19% due to infections (95% CI 1–33%), and no change for the other diagnoses, compared to 2017–2019. The risk of in-hospital mortality to total mortality was lower for acute myocardial infarction (relative risk 0.85, 95% CI 0.73–0.99) and injuries (relative risk 0.83, 95% CI 0.70–0.98). Conclusions: Even though fewer patients were admitted to hospital, there was no increase in in-hospital fatality or population mortality, indicating that those who were most in need still received adequate care.

• Schult, Anna Lisa; Botteri, Edoardo; Hoff, Geir; Holme, Øyvind; Bretthauer, Michael & Randel, Kristin Ranheim [Show all 13 contributors for this article] (2021). Women require routine opioids to prevent painful colonoscopies: a randomised controlled trial. Scandinavian Journal of Gastroenterology. ISSN 0036-5521. 56(12), p. 1480–1489. doi: 10.1080/00365521.2021.1969683. Full text in Research Archive Show summary

  Background: Women are at high risk for painful colonoscopy. Pain, but also sedation, are barriers to colorectal cancer (CRC) screening participation. In a randomised controlled trial, we compared on-demand with pre-colonoscopy opioid administration to control pain in women at CRC screening age. Methods: Women, aged 55-79 years, attending colonoscopy at two Norwegian endoscopy units were randomised 1:1:1 to (1) fentanyl on-demand, (2) fentanyl prior to colonoscopy, or (3) alfentanil on-demand. The primary endpoint was procedural pain reported by the patients on a validated four-point Likert scale and further dichotomized for the study into painful (moderate or severe pain) and non-painful (slight or no pain) colonoscopy. Secondary endpoints were: willingness to repeat colonoscopy, adverse events, cecal intubation time and rate, and post-procedure recovery time. Results: Between June 2017 and May 2020, 183 patients were included in intention-to-treat analyses in the fentanyl on-demand group, 177 in the fentanyl prior to colonoscopy group, and 179 in the alfentanil on-demand group. Fewer women receiving fentanyl prior to colonoscopy reported a painful colonoscopy compared to those who were given fentanyl on-demand (25.2% vs. 44.1%, p

• Jodal, Henriette C.; Klotz, Dagmar; Herfindal, Magnhild; Barua, Ishita; Tag, Petter & Helsingen, Lise Mørkved [Show all 12 contributors for this article] (2021). Long-term colorectal cancer incidence and mortality after adenoma removal in women and men. Alimentary Pharmacology and Therapeutics. ISSN 0269-2813. p. 1–10. doi: 10.1111/apt.16686. Full text in Research Archive
• Juul, Frederik E.; Jodal, Henriette C.; Barua, Ishita; Refsum, Erle; Olsvik, Ørjan & Helsingen, Lise Mørkved [Show all 10 contributors for this article] (2021). Mortality in Norway and Sweden during the COVID-19 pandemic. Scandinavian Journal of Public Health. ISSN 1403-4948. p. 1–8. doi: 10.1177/14034948211047137. Full text in Research Archive Show summary

  Background: Norway and Sweden are similar countries in terms of socioeconomics and health care. Norway implemented extensive COVID-19 measures, such as school closures and lockdowns, whereas Sweden did not. Aims: To compare mortality in Norway and Sweden, two similar countries with very different mitigation measures against COVID-19. <p> <p>Methods: Using real-world data from national registries, we compared all-cause and COVID-19-related mortality rates with 95% confidence intervals (CI) per 100,000 person-weeks and mortality rate ratios (MRR) comparing the five preceding years (2015–2019) with the pandemic year (2020) in Norway and Sweden. <p> <p>Results: In Norway, all-cause mortality was stable from 2015 to 2019 (mortality rate 14.6–15.1 per 100,000 person-weeks; mean mortality rate 14.9) and was lower in 2020 than from 2015 to 2019 (mortality rate 14.4; MRR 0.97; 95% CI 0.96–0.98). In Sweden, all-cause mortality was stable from 2015 to 2018 (mortality rate 17.0–17.8; mean mortality rate 17.1) and similar to that in 2020 (mortality rate 17.6), but lower in 2019 (mortality rate 16.2). Compared with the years 2015–2019, all-cause mortality in the pandemic year was 3% higher due to the lower rate in 2019 (MRR 1.03; 95% CI 1.02–1.04). Excess mortality was confined to people aged ⩾70 years in Sweden compared with previous years. The COVID-19-associated mortality rates per 100,000 person-weeks during the first wave of the pandemic were 0.3 in Norway and 2.9 in Sweden. <p> <p>Conclusions: All-cause mortality in 2020 decreased in Norway and increased in Sweden compared with previous years. The observed excess deaths in Sweden during the pandemic may, in part, be explained by mortality displacement due to the low all-cause mortality in the previous year.

• Helsingen, Lise Mørkved; Løberg, Magnus; Refsum, Erle; Gjøstein, Dagrun Kyte; Wieszczy, Paulina & Olsvik, Ørjan [Show all 16 contributors for this article] (2021). Covid-19 transmission in fitness centers in Norway - a randomized trial. BMC Public Health. 21, p. 1–9. doi: 10.1186/s12889-021-12073-0. Full text in Research Archive Show summary

  Background: Closed fitness centers during the Covid-19 pandemic may negatively impact health and wellbeing. We assessed whether training at fitness centers increases the risk of SARS-CoV-2 virus infection.<p> <p>Methods: In a two-group parallel randomized controlled trial, fitness center members aged 18 to 64 without Covid-19-relevant comorbidities, were randomized to access to training at a fitness center or no-access. Fitness centers applied physical distancing (1 m for floor exercise, 2 m for high-intensity classes) and enhanced hand and surface hygiene. Primary outcomes were SARS-CoV-2 RNA status by polymerase chain reaction (PCR) after 14 days, hospital admission after 21 days. The secondary endpoint was SARS-CoV-2 antibody status after 1 month.<p> <p>Results: 3764 individuals were randomized; 1896 to the training arm and 1868 to the no-training arm. In the training arm, 81.8% trained at least once, and 38.5% trained ≥six times. Of 3016 individuals who returned the SARSCoV-2 RNA tests (80.5%), there was one positive test in the training arm, and none in the no-training arm (risk difference 0.053%; 95% CI − 0.050 to 0.156%; p = 0.32). Eleven individuals in the training arm (0.8% of tested) and 27 in the no-training arm (2.4% of tested) tested positive for SARS-CoV-2 antibodies (risk difference − 0.87%; 95%CI − 1.52% to − 0.23%; p = 0.001). No outpatient visits or hospital admissions due to Covid-19 occurred in either arm.<p> <p>Conclusion: Provided good hygiene and physical distancing measures and low population prevalence of SARS-CoV-2 infection, there was no increased infection risk of SARS-CoV-2 in fitness centers in Oslo, Norway for individuals without Covid-19-relevant comorbidities.

• Barua, Ishita; Mori, Yuichi & Bretthauer, Michael (2020). Colorectal polyp characterization with endocytoscopy: Ready for widespread implementation with artificial intelligence? Baillière's Best Practice & Research Clinical Gastroenterology. ISSN 1521-6918. doi: 10.1016/j.bpg.2020.101721. Full text in Research Archive
• Barua, Ishita; Vinsard, Daniela Guerrero; Jodal, Henriette C.; Løberg, Magnus; Kalager, Mette & Holme, Øyvind [Show all 9 contributors for this article] (2020). Artificial intelligence for polyp detection during colonoscopy: A systematic review and meta-analysis. Endoscopy. ISSN 0013-726X. doi: 10.1055/a-1201-7165. Full text in Research Archive
• Schult, Anna Lisa; Randel, Kristin Ranheim; Barua, Ishita; Svendsen, Hege Marie; Bernklev, Linn & Sandvei, Per [Show all 9 contributors for this article] (2018). Screening mot tarmkreft i hele Norge. Indremedisineren. ISSN 1891-1617. 2, p. 25–29. Full text in Research Archive

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• Wivestad, Viggo Tellefsen & Barua, Ishita (2026). NRK Ekko i P2 (27. juni 2026). [Radio]. NRK P2. doi: https:/radio.nrk.no/serie/ekko/IFAK02012326. Show summary

  Bruken av KI vekkjer sterke kjensler og store overskrifter både i form av glede og forrakt, og det verkar som det er veldig ulike oppfatningar om når det er greitt og ikkje å bruke det, så vi vil med spørjetimen få KI-ekspertane sjølv til å hjelpe oss med å vurdere dette.

• Wivestad, Viggo Tellefsen & Barua, Ishita (2026). NRK Ekko i P2 (2. juni 2026). [Radio]. NRK. doi: https:/radio.nrk.no/serie/ekko/IFAK02008626. Full text in Research Archive Show summary

  Spør Ekko: Når er det greit å bruke KI?

• Einevoll, Gaute & Barua, Ishita (2024). #95: Om bruk av AI i helsevesenet - med Ishita Barua. [Internet]. Podcast "Vett og vitenskap". Full text in Research Archive
• Barua, Ishita & Lund, Mass Soldal (2024). Kan kunstig intelligens redde liv? Full text in Research Archive
• Goodwin, Morten & Barua, Ishita (2024). Kunstig intelligens redder liv. Full text in Research Archive
• Wahl, Andreas; Skogvoll, Vidar & Barua, Ishita (2022). Jøss‽ - #54 - Fridtjof i dødt vann, frosne sitrontrær og narkolegen. [Radio]. Podcast. Full text in Research Archive
• Wahl, Andreas Solberg; Skogvoll, Vidar & Barua, Ishita (2022). Jøss‽ - #59 - Ett nevron mindre, drittdag på jobb og effekten av hjemmeskole. [Radio]. Podcast. Full text in Research Archive
• Strumke, Inga & Barua, Ishita (2022). Hvordan kan vi holde algoritmene i ørene? Forskningsmiljøer står klare til å hjelpe. Full text in Research Archive
• Barua, Ishita; Goodwin, Morten; Brøgger, Helga Maria; Pettersen, Klas Henning & Fattah, Ida Susanna (2021). Verdien av kunstig intelligens i helse. Full text in Research Archive
• Barua, Ishita & Strumke, Inga (2021). Utviklere av kunstig intelligens må få det leger har. Nemlig en profesjonsetikk. Full text in Research Archive
• Barua, Ishita (2021). Når skal Norge engasjere seg i EU-forslaget om kunstig intelligens? Full text in Research Archive
• Schreurs, Nard & Barua, Ishita (2021). En avmystifisering av AI, algoritmer og BigData. [Internet]. https://ehin.no/artikler/en-avmystifisering-av-ai-algoritmer. Full text in Research Archive
• Barua, Ishita (2021). Utviklere av kunstig intelligens må få det leger har. Nemlig en profesjonsetikk. Full text in Research Archive
• Barua, Ishita (2020). Kreftdagen: Ti viktige fakta om tykktarmskreft. Medisinbloggen. Full text in Research Archive
• Barua, Ishita; Berset, Ingrid Prytz; Hære, Petter; Wensaas, Knut-Arne & Bretthauer, Michael (2020). Nasjonalt screeningprogram for tarmkreft. Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. 140(3), p. 222–222. doi: 10.4045/tidsskr.19.0658. Full text in Research Archive
• Barua, Ishita (2020). EHiN 2020: Implementering av AI i norsk helsevesen. Full text in Research Archive
• Barua, Ishita (2020). Digitalt fagseminar for Kommunikasjonsforeningen: Ta i med AI – en innføring i hva algoritmer og kunstig intelligens betyr for oss i fremtiden. Full text in Research Archive
• Barua, Ishita (2020). Kunstig intelligens – legenes nye superkrefter. Full text in Research Archive
• Barua, Ishita; Chaffey, Paul & Skogen, Mali (2020). Universitetsplassen LIVE: Trenger vi et etisk råd for kunstig intelligens? [Internet]. https://www.uio.no/om/aktuelt/universitetsplassen/arrangemen. Full text in Research Archive
• Barua, Ishita (2020). Hvem overvåker overvåkerne? Full text in Research Archive
• Stensland, Marianne; Barua, Ishita & Mori, Yuichi (2020). Fra 2021 skal nordmenn masseundersøkes for tarmkreft. Ny teknologi kan gjøre det billigere og bedre. [Journal]. Aftenposten. Full text in Research Archive
• Barua, Ishita (2020). Innlegg: Må holde algoritmene i ørene – tid for råd og regulering. Full text in Research Archive
• Barua, Ishita (2020). Algoritmene har stort skadepotensial. Full text in Research Archive
• Barua, Ishita (2020). God morgen Norge, TV 2. [TV]. TV 2. Full text in Research Archive Show summary

  Intervju på TV 2 i programmet "God morgen Norge" om Bioteknologirådets innstilling til eggdonasjon og assistert befruktning for enslige.

• Barua, Ishita & Vevle, Frank (2020). Medisin og kunstig intelligens med Ishita Barua. [Radio]. Podcast AICAST . Full text in Research Archive Show summary

  AICAST Frank Vevle, Michael Løiten En podcast fra fagkomiteen for AI (kunstig intelligens) i Den Norske Dataforening.

• Barua, Ishita (2020). Kunstig intelligens innenfor medisin og helsevesenet. Full text in Research Archive Show summary

  Gjesteforelesning for HONORS-studentene på UiO

• Slagstad, Ketil & Barua, Ishita (2020). Mye hype, men lite kunnskap om kunstig intelligens. [Journal]. Tidsskriftet. Full text in Research Archive
• Barua, Ishita (2020). Podcast: Studentersamfunnet om robotlegen. [Radio]. Spotify. Full text in Research Archive
• Barua, Ishita (2019). MEDEVENT 2019: Kunstig intelligens innen helse (Keynote). Full text in Research Archive
• Barua, Ishita (2019). Livsviktige data: Kunstig intelligens i medisin. Medisinbloggen. Full text in Research Archive
• Barua, Ishita (2019). EHiN 2019: Kunstig intelligens innen helsevesenet. Full text in Research Archive
• Barua, Ishita (2019). Three ways Finland leads the world - and education isn't one of them. Full text in Research Archive
• Barua, Ishita; Glomsrød, Maren; Martinaityte, Ieva & Sarna, Vikas Kumar (2019). Vårmøte og kurs for leger i spesialisering i indremedisin. Indremedisineren. ISSN 1891-1617. 2, p. 42–43. Full text in Research Archive
• Barua, Ishita (2019). Arbeiderklassen trengs i akademia. Full text in Research Archive
• Barua, Ishita (2019). Arbeiderklassen trengs i akademia. Full text in Research Archive
• Seres, Silvija & Barua, Ishita (2019). Kunstig intelligens innen helsevesenet. [Radio]. LØRN.Tech (Podcast). Full text in Research Archive
• Barua, Ishita (2019). Arbeiderklassen trengs i akademia. Full text in Research Archive
• Barua, Ishita (2018). Kunstig intelligens kan i verste fall gjøre oss mindre intelligente. Full text in Research Archive
• Slørdahl, Johannes Thomassen & Barua, Ishita (2013). Er innføring av karakterer veien å gå? Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. doi: 10.4045/tidsskr.13.1231. Full text in Research Archive

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