[{"data":1,"prerenderedAt":161},["ShallowReactive",2],{"slug-what-ai-can-already-do-in-healthcare-in-8-examples":3},{"post":4,"relatedPosts":159,"relatedBooks":160},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":32,"project_category":33,"contact_email_category":34,"yst_prominent_words":35,"class_list":45,"better_featured_image":53,"acf":98,"yoast_meta":104,"_links":106},58255,"2026-06-04T08:56:31","2026-06-04T06:56:31",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=58255&_wpnonce=83a763ce88&status=auto-draft&type=post","2026-06-09T08:05:04","2026-06-09T06:05:04","what-ai-can-already-do-in-healthcare-in-8-examples","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fwhat-ai-can-already-do-in-healthcare-in-8-examples",{"rendered":17},"What AI Can Already Do In Healthcare In 8 Examples",{"rendered":19,"protected":20},"\n\u003Cp>There has been a lot of buzz around artificial intelligence (AI); and the healthcare field is no stranger. The promise of the technology range from \u003Ca href=\"https:\u002F\u002Fhitconsultant.net\u002F2024\u002F11\u002F25\u002Fhealthcare-as-a-right-how-ai-is-shaping-global-access\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">addressing the shortage\u003C\u002Fa> of healthcare providers to \u003Ca href=\"https:\u002F\u002Fwww.mckinsey.com\u002Findustries\u002Fhealthcare\u002Four-insights\u002Fgenerative-ai-in-healthcare-adoption-trends-and-whats-next\" target=\"_blank\" rel=\"noreferrer noopener\">improving patient engagement\u003C\u002Fa> in their care. \u003C\u002Fp>\n\n\n\n\u003Cp>Among such promises, it might be challenging to identify the current uses of AI in healthcare. In order to better understand the upcoming potentials of the technology, it is important to understand its current state.\u003C\u002Fp>\n\n\n\n\u003Cp>In this article, we put AI’s current potentials in perspective by sharing a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">1. Generating clinical notes during consultations\u003C\u002Fh2>\n\n\n\n\u003Cp>On average, physicians spend \u003Ca href=\"https:\u002F\u002Fpubmed.ncbi.nlm.nih.gov\u002F31931523\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">16 minutes per patient encounter\u003C\u002Fa> on electronic health records. Some of this documentation \u003Ca href=\"https:\u002F\u002Fwww.lyrebirdhealth.com\u002Fuk\u002Fblogs\u002Ftop-4-best-ai-medical-scribes\" target=\"_blank\" rel=\"noreferrer noopener\">can be automated by AI technology\u003C\u002Fa> to save hours for healthcare professionals and also reduce the risk of burnout.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-768x432.png\" alt=\"\" class=\"wp-image-52835\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-370x208.png 370w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388-1536x864.png 1536w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F10\u002Ftmf_article_388.png 1920w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>Real-time transcription and summarization tools like \u003Ca href=\"https:\u002F\u002Fwww.nuance.com\u002Fhealthcare\u002Fdragon-ai-clinical-solutions\u002Fdax-copilot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Nuance’s DAX Copilot\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.lyrebirdhealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Lyrebird Health\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.ambiencehealthcare.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Ambiance\u003C\u002Fa> can automatically document patient encounters. By using speech recognition and natural language processing (NLP), they recognise clinical conversations, extract relevant information and generate summaries. In the case of DAX Copilot, \u003Ca href=\"https:\u002F\u002Fwww.nuance.com\u002Fhealthcare\u002Fdragon-ai-clinical-solutions\u002Fdax-copilot.html\" target=\"_blank\" rel=\"noreferrer noopener\">70% of users report\u003C\u002Fa> improved work-life balance and a reduction in feeling of burnout.\u003C\u002Fp>\n\n\n\n\u003Cp>However, there is \u003Ca href=\"https:\u002F\u002Fapnews.com\u002Farticle\u002Fai-artificial-intelligence-health-business-90020cdf5fa16c79ca2e5b6c4c9bbb14\" target=\"_blank\" rel=\"noreferrer noopener\">the risk of hallucination\u003C\u002Fa> with such tools. This can be a reason for significant concern in a healthcare setting and this highlights the need for the AI summary to be reviewed by humans.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">2. Analysing radiology scans \u003C\u002Fh2>\n\n\n\n\u003Cp>Radiology is among the first medical fields to \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-radiology-and-ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">adopt AI in its midst\u003C\u002Fa>. Companies like \u003Ca href=\"https:\u002F\u002Fwww.aidoc.com\u002Fsolutions\u002Fradiology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Aidoc\u003C\u002Fa> and \u003Ca href=\"http:\u002F\u002Fqure.ai\" target=\"_blank\" rel=\"noreferrer noopener\">Qure.ai\u003C\u002Fa> have developed AI tools that can identify abnormalities in radiology images with high accuracy. \u003C\u002Fp>\n\n\n\n\u003Cp>The AI-driven diagnostics tool from Qure.ai processes \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Ftonybradley\u002F2024\u002F09\u002F29\u002Ftransforming-radiology-with-ai-powered-diagnostics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">around 10 million scans\u003C\u002Fa> every year across more than 90 countries. In the Philippines, the technology has \u003Ca href=\"https:\u002F\u002Fwww.forbes.com\u002Fsites\u002Ftonybradley\u002F2024\u002F09\u002F29\u002Ftransforming-radiology-with-ai-powered-diagnostics\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">slashed the wait times\u003C\u002Fa> for tuberculosis diagnosis from weeks to seconds.\u003C\u002Fp>\n\n\n\n\u003Cp>Such tools aren’t favoured by every radiologists though, as \u003Ca href=\"https:\u002F\u002Fhms.harvard.edu\u002Fnews\u002Fdoes-ai-help-or-hurt-human-radiologists-performance-depends-doctor\" target=\"_blank\" rel=\"noreferrer noopener\">recent studies\u003C\u002Fa> have shown. AI can help some radiologists’ performance but it can also worsen that of others. This indicates the need to calibrate such tools to individual preference in order to maximise benefits.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">3. Triaging patients \u003C\u002Fh2>\n\n\n\n\u003Cp>Triaging \u003Ca href=\"https:\u002F\u002Fwww.verywellhealth.com\u002Fmedical-triage-and-how-it-works-2615132\" target=\"_blank\" rel=\"noreferrer noopener\">involves the initial assessment\u003C\u002Fa> of patients’ condition to determine their priority of care and the adequate healthcare professional they need to consult. Traditionally, this has been undertaken on a first-come-first-served basis and can take several hours’ of patients’ time. AI tools can make triaging more efficient and equitable based on individual clinical needs.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"768\" height=\"432\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-768x432.png\" alt=\"medical chatbot AI algorithm person man phone TMF\" class=\"wp-image-48671\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-768x432.png 768w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2023\u002F01\u002Ftmf_article_348-01-370x208.png 370w\" sizes=\"auto, (max-width: 768px) 100vw, 768px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cp>Tools like \u003Ca href=\"https:\u002F\u002Fada.com\u002Fimproving-patient-pathways-with-ada-digital-triage\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Ada Health\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.rapidhealth.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Rapid Health’s Smart Triage\u003C\u002Fa> use AI to assess symptoms and recommend appropriate care pathways. An \u003Ca href=\"https:\u002F\u002Fwww.med-technews.com\u002Fnews\u002FDigital-in-Healthcare-News\u002Fai-triage-system-achieves-73-reduction-in-waiting-times-according-to-nhs-study\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">independent study\u003C\u002Fa> investigating the Smart Triage system found that the tool reduced patient waiting times by 73%, improved practice capacity and significantly streamlined appointments with sustainable staff working patterns.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">4. Controlling assistive robots\u003C\u002Fh2>\n\n\n\n\u003Cp>In many instances, robots have been adopted as “medical staff” to \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fthe-future-of-nurses-superheros-aided-by-technology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">handle monotonous tasks\u003C\u002Fa> and AI can further assist in their tasks. The \u003Ca href=\"https:\u002F\u002Fwww.servicerobotics.ai\u002Frichtech\u002Fmedbot.html\" target=\"_blank\" rel=\"noreferrer noopener\">Medbot\u003C\u002Fa> from Richtech Robotics and Unlimited Robotics’ \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Gary\u003C\u002Fa> are robots that can assist in logistics tasks within healthcare institutions such as delivering medications and general supplies. \u003C\u002Fp>\n\n\n\n\u003Cp>Medbot has an AI platform that helps the robot integrate in the workflow of organisations and streamline operations. Gary, which is also capable of disinfecting hospital rooms, \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">has been found to\u003C\u002Fa> increase nurses’ time with patients and improve staff productivity.\u003C\u002Fp>\n\n\n\n\u003Cp>While such robots can \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002Fpost\u002Frevolutionizing-hospital-inventory-management-how-ai-powered-robotics-can-solve-the-5-billion-prob\" target=\"_blank\" rel=\"noreferrer noopener\">optimise hospitals’ supply chain practices\u003C\u002Fa> and save costs, they might not be accessible to every healthcare institution due to their upfront cost. Depending on hospital size and complexity, the cost to implement a system like Gary can Gary can range \u003Ca href=\"https:\u002F\u002Fwww.hospital-robots.com\u002Fpost\u002Frevolutionizing-hospital-inventory-management-how-ai-powered-robotics-can-solve-the-5-billion-prob\" target=\"_blank\" rel=\"noreferrer noopener\">between $2–5 million\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">5. Analysing pathology scans and samples\u003C\u002Fh2>\n\n\n\n\u003Cp>In recent years, the field of pathology has received an uplift with the advent of \u003Ca href=\"https:\u002F\u002Fmedicalfuturist.com\u002Fdigital-future-pathology\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">digital pathology\u003C\u002Fa>. This replaces traditional microscope-based manual tissue analyses with \u003Ca href=\"https:\u002F\u002Fhealthcare-in-europe.com\u002Fen\u002Fnews\u002Fdigital-pathology-ai-platform-lung-cancer-diagnosis.html\" target=\"_blank\" rel=\"noreferrer noopener\">digitised tissue sections\u003C\u002Fa> that can be investigated on a computer screen. Such an approach can benefit from AI integration which can be used to apply advanced analytical methods.\u003C\u002Fp>\n\n\n\n\u003Cp>Platforms like \u003Ca href=\"https:\u002F\u002Fpaige.ai\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Paige\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.pathai.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">PathAI\u003C\u002Fa> help pathologists detect cancer and other abnormalities with precision. With Paige’s AI model, pathologists have experienced \u003Ca href=\"https:\u002F\u002Fmeridian.allenpress.com\u002Faplm\u002Farticle\u002F147\u002F10\u002F1178\u002F489438\u002FClinical-Validation-of-Artificial-Intelligence\" target=\"_blank\" rel=\"noreferrer noopener\">up to 70% reduction\u003C\u002Fa> in cancer detection errors. The tool can also reduce the time to diagnosis \u003Ca href=\"https:\u002F\u002Fpathsocjournals.onlinelibrary.wiley.com\u002Fdoi\u002Ffull\u002F10.1002\u002Fpath.5662\" target=\"_blank\" rel=\"noreferrer noopener\">by 65.5%\u003C\u002Fa>.\u003C\u002Fp>\n\n\n\n\u003Cp>Researchers also favour the integration of AI in pathology but \u003Ca href=\"https:\u002F\u002Fdiagnosticpathology.biomedcentral.com\u002Farticles\u002F10.1186\u002Fs13000-023-01375-z\" target=\"_blank\" rel=\"noreferrer noopener\">highlight the need\u003C\u002Fa> to implement the technology under standardized usage recommendations and harmonisation with current information systems.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">6. Detecting risk of falls using video cameras\u003C\u002Fh2>\n\n\n\n\u003Cp>Despite being preventable, falls are a common cause of injury, especially among the elderly. According to the CDC, \u003Ca href=\"https:\u002F\u002Fwww.cdc.gov\u002Ffalls\u002Fdata-research\u002Findex.html\" target=\"_blank\" rel=\"noreferrer noopener\">1 in 4 older adults\u003C\u002Fa> report falling every year which, in some cases, can lead to death. Systems like the AI-powered \u003Ca href=\"https:\u002F\u002Fkamivision.com\u002Fen-us\u002Ffall-detection\u002Fassisted-living-kamicare\" target=\"_blank\" rel=\"noreferrer noopener\">Fall Detection solution by KamiCare\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.averusa.com\u002Fproducts\u002Fptz-camera\u002Fmd720uis\" target=\"_blank\" rel=\"noreferrer noopener\">AVer MD720UIS camera\u003C\u002Fa> monitor movement and assess fall risk in elderly patients. When a fall is detected, the system immediately alerts health teams to respond promptly and ensure patient safety.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed aligncenter is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"High-tech hospital uses artificial intelligence in patient care\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FqetKUFDDF4A?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>As these solutions rely on a camera, privacy concerns arise. Measures that these companies have taken to ensure privacy include blurring faces to only detect movements.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">7. Performing therapy as chatbots \u003C\u002Fh2>\n\n\n\n\u003Cp>Access to mental health services remains a challenge, with such services not reaching \u003Ca href=\"https:\u002F\u002Fwww.news-medical.net\u002Fhealth\u002FArtificial-Intelligence-in-CBT.aspx\" target=\"_blank\" rel=\"noreferrer noopener\">as many as 70%\u003C\u002Fa> needing them. Furthermore, the WHO estimates that high-income countries have \u003Ca href=\"https:\u002F\u002Fwww.who.int\u002Fnews\u002Fitem\u002F08-10-2021-who-report-highlights-global-shortfall-in-investment-in-mental-health\" target=\"_blank\" rel=\"noreferrer noopener\">over 40 times more\u003C\u002Fa> mental health workers than low-income countries. \u003C\u002Fp>\n\n\n\n\u003Cp>To improve access to mental health services, companies have leveraged AI technology. Apps like \u003Ca href=\"https:\u002F\u002Fwoebothealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">Woebot\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fwww.wysa.com\u002Fai-cbt\" target=\"_blank\" rel=\"noreferrer noopener\">Wysa\u003C\u002Fa> provide AI-driven cognitive behavioral therapy (CBT) support for patients in need of them. Woebot found that \u003Ca href=\"https:\u002F\u002Fwoebothealth.com\u002F\" target=\"_blank\" rel=\"noreferrer noopener\">75% of its users\u003C\u002Fa> employ the app outside of traditional working hours or during weekends. This shows that access to mental health support can be improved when it is needed the most with such AI-based approaches.\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\">\u003Cdiv class=\"wp-block-embed__wrapper\">\n\u003Ciframe loading=\"lazy\" title=\"Woebot Demo\" width=\"640\" height=\"360\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FrrHyFnYWrk4?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen>\u003C\u002Fiframe>\n\u003C\u002Fdiv>\u003C\u002Ffigure>\n\n\n\n\u003Cp>It’s important to note that such apps function\u003Ca href=\"https:\u002F\u002Fspectrum.ieee.org\u002Fwoebot\" target=\"_blank\" rel=\"noreferrer noopener\"> as support tools\u003C\u002Fa> to be used in tandem with human support. They also won’t cover the whole range of therapies that professionals can provide but they do offer support in a field that is facing severe accessibility challenges.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">8. Predicting patient deterioration in real-time\u003C\u002Fh2>\n\n\n\n\u003Cp>Early signs of patient deterioration can be subtle and challenging for clinical teams to identify. Up to \u003Ca href=\"https:\u002F\u002Fjamanetwork.com\u002Fjournals\u002Fjamanetworkopen\u002Ffullarticle\u002F2824885\" target=\"_blank\" rel=\"noreferrer noopener\">5% of hospitalized patients\u003C\u002Fa> can experience signs of clinical deterioration but delays in adequate care can increase the length of stays or even mortality. \u003C\u002Fp>\n\n\n\n\u003Cp>Tools like the \u003Ca href=\"https:\u002F\u002Fwww.epicshare.org\u002Fshare-and-learn\u002Fsaving-lives-with-ai\" target=\"_blank\" rel=\"noreferrer noopener\">Epic Deterioration Index\u003C\u002Fa> use AI to monitor patient vitals and flag critical conditions in ICUs. In a Novant Health facility, \u003Ca href=\"https:\u002F\u002Fwww.epicshare.org\u002Fshare-and-learn\u002Fsaving-lives-with-ai\">the tool has helped\u003C\u002Fa> reduce mortality by 22% and saved about 153 lives over 11 months.\u003C\u002Fp>\n\n\n\n\u003Cp>Other similar options include \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.agilemd.com\u002F\" target=\"_blank\">eCART from AgileMD\u003C\u002Fa> and \u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\">Per\u003C\u002Fa>\u003Ca href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\" rel=\"noreferrer noopener\">a\u003C\u002Fa>\u003Ca rel=\"noreferrer noopener\" href=\"https:\u002F\u002Fwww.businesswire.com\u002Fnews\u002Fhome\u002F20180503005425\u002Fen\u002FPeraHealth-Receives-U.S.-FDA-510-k-Clearance-for-Industry-Leading-Clinical-Surveillance-Technology\" target=\"_blank\">Trend from PeraHealth\u003C\u002Fa>. Researchers have even found that eCART can perform \u003Ca href=\"https:\u002F\u002Fjamanetwork.com\u002Fjournals\u002Fjamanetworkopen\u002Ffullarticle\u002F2824885\">better than\u003C\u002Fa> Epic’s tool. We can expect such tools to become even more accurate at determining patients’ health status as their predicting prowess improves over time.\u003C\u002Fp>\n\n\n\u003Cdiv class=\"wp-block-image\">\n\u003Cfigure class=\"aligncenter size-full\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"720\" height=\"405\" src=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png\" alt=\"fake drugs counterfeit medicine\" class=\"wp-image-40965\" srcset=\"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2.png 720w, https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2022\u002F03\u002Ffake-drugs2-370x208.png 370w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \u002F>\u003C\u002Ffigure>\n\u003C\u002Fdiv>\n\n\n\u003Cp>We hope that you have found these examples where AI is already used in practice insightful! We will be back with another article in this series that focuses on what AI can bring to healthcare in the near future. Stay tuned for it!\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Written by Dr. Bertalan Meskó & Dr. Pranavsingh Dhunnoo\u003C\u002Fem>\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>In this article, we put AI’s current potentials in perspective by sharing a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n",16,55953,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31],504,[],[],[],[36,37,38,39,40,41,42,43,44],1631,1683,1719,1803,1833,2369,3579,1559,1571,[46,14,47,48,49,50,51,52],"post-58255","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence",{"id":24,"alt_text":54,"caption":27,"description":54,"media_type":55,"media_details":56,"post":96,"source_url":97},"AI, radiology, doctor, X-ray","image",{"width":57,"height":58,"file":59,"filesize":60,"sizes":61,"image_meta":93},6667,3750,"2024\u002F05\u002Ftmf_article_413.png",570989,{"medium":62,"large":69,"thumbnail":75,"medium_large":80,"1536x1536":81,"2048x2048":87},{"file":63,"width":64,"height":65,"mime-type":66,"filesize":67,"source_url":68},"tmf_article_413-370x208.png",370,208,"image\u002Fpng",27111,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-370x208.png",{"file":70,"width":71,"height":72,"mime-type":66,"filesize":73,"source_url":74},"tmf_article_413-768x432.png",768,432,65695,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-768x432.png",{"file":76,"width":77,"height":77,"mime-type":66,"filesize":78,"source_url":79},"tmf_article_413-150x150.png",150,16352,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-150x150.png",{"file":70,"width":71,"height":72,"mime-type":66,"filesize":73,"source_url":74},{"file":82,"width":83,"height":84,"mime-type":66,"filesize":85,"source_url":86},"tmf_article_413-1536x864.png",1536,864,148847,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-1536x864.png",{"file":88,"width":89,"height":90,"mime-type":66,"filesize":91,"source_url":92},"tmf_article_413-2048x1152.png",2048,1152,207612,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413-2048x1152.png",{"aperture":94,"credit":27,"camera":27,"caption":27,"created_timestamp":94,"copyright":27,"focal_length":94,"iso":94,"shutter_speed":94,"title":27,"orientation":94,"keywords":95},"0",[],17898,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2024\u002F05\u002Ftmf_article_413.png",{"subtitle":27,"key_takeaways":99,"cta_type":27,"cta_color":27,"related_books":20,"related_posts_footer":20,"related_posts":20},[100,102],{"title":101},"\u003Cp>With the ongoing buzz around AI’s potential in healthcare, it can be challenging to identify its current uses.\u003C\u002Fp>\n",{"title":103},"\u003Cp>We share a collection of 8 examples where the technology already exists in practice.\u003C\u002Fp>\n",{"yoast_wpseo_title":105,"yoast_wpseo_metadesc":27,"yoast_wpseo_canonical":15},"What AI Can Already Do In Healthcare In 8 Examples - 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