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Artificial Intelligence and Machine Learning for Healthcare and Anesthesiology

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Introduction

Technological innovations like Artificial Intelligence and Machine learning allow the detection of valuable patterns within large datasets which – after been subjected to enough data – allows the algorithms to perform predictions on previously unseen data subjects. Such intelligent software has been used extensively in different fields of the healthcare industry – including neurology, cardiology, and oncology – with the purpose of aiding medical personnel with disease diagnostics, disease prevention, and personalized medical treatment [1].

However, previous attempts to incorporate machine learning within anesthesiology – which is the field within the healthcare industry that focuses on providing perioperative care to patients – have been unsuccessful [2]. This article will provide an overview of the difficulties that arise when automating the field of anesthesiology.


Difficulties with automating anesthesiology procedures

Generally, systems for the automation of anesthesiology procedures rely on a closed-loop feedback system which is able to successfully keep a quantifiable target measure – usually the bispectral index (BIS) when assessing depth of anesthesia – within a pre-defined range [1] [3]. Using various drug administration rates – which depend on the measured BIS level – the patient’s level of consciousness can be controlled in an autonomous way.

Various studies have shown that the use of such closed-loop feedback systems could be beneficial in the context of keeping the patient’s level of consciousness within a pre-determined BIS range, with the additional benefit of providing a lower dose of anesthetic in comparison to the human-controlled case [4] [5] [6]. Whereas there is evidence that closed-loop feedback systems are feasible to assist in guaranteeing required anesthetic levels for both simple and more complex cases [7], they by no means are able to fully automate the – usually human-controlled – process.

However, innovations such as Artificial Intelligence – which implement a bottom-up rather than a top-down approach like rule-based feedback loops – are able to learn to take the required patient’s level of consciousness actions from real-world patient data without being explicitly programmed to. Whereas these algorithms are able to tackle tasks that are much more complex in comparison to rule-based systems, in practice they still possess flaws which require the need of a professional anesthetist during medical interventions:

  1. Artificial Intelligence is especially well-suited for performing cognitive tasks (i.e., carrying out accurate predictions and crunching large data sets). However, the technology is yet unable to deliver the dexterity-based labor that is involved with the field of anesthesiology. [8]
  • Artificial Intelligence and Machine Learning – implemented in robotic devices – do not have the finesse to deal with complex tasks such as neural blockades, venous cannulation or tracheal intubation. [8]
  • The field of anesthesiology is characterized by providing micro-doses in order to remain the required level of patient consciousness. However, patients are uncomfortable with the thought of replacing a human anesthetist with fully autonomous decision-making software without human control.

Conclusion

Whereas current procedures – such as rule-based systems or artificial intelligence – are yet unable to fully take over human anesthetic tasks, they are thought to play a major role in the future of anesthesiology. Computer software – powered by artificial intelligence – will ultimately aid in all decisions made by anesthetist and, when innovations in robotics allow it, take over dexterity-based labor as well.

References

[1] Murali, Nivetha & Sivakumaran, Nivethika. (2018). Artificial Intelligence in Healthcare-A Review. 10.13140/RG.2.2.27265.92003.

[2] Alexander, J. C., & Joshi, G. P. (2018, January). Anesthesiology, automation, and artificial intelligence. In Baylor University Medical Center Proceedings (Vol. 31, No. 1, pp. 117-119). Taylor & Francis.

[3] Kissin, I. (2000). Depth of anesthesia and bispectral index monitoring. Anesthesia & Analgesia90(5), 1114-1117.

[4] Brogi, E., Cyr, S., Kazan, R., Giunta, F., & Hemmerling, T. M. (2017). Clinical performance and safety of closed-loop systems: a systematic review and meta-analysis of randomized controlled trials. Anesthesia & Analgesia124(2), 446-455.

[5] Pasin, L., Nardelli, P., Pintaudi, M., Greco, M., Zambon, M., Cabrini, L., & Zangrillo, A. (2017). Closed-loop delivery systems versus manually controlled administration of total IV anesthesia: a meta-analysis of randomized clinical trials. Anesthesia & Analgesia124(2), 456-464.

[6] Puri, G. D., Mathew, P. J., Biswas, I., Dutta, A., Sood, J., Gombar, S., … & Arora, I. (2016). A multicenter evaluation of a closed-loop anesthesia delivery system: a randomized controlled trial. Anesthesia & Analgesia122(1), 106-114.

[7] Zaouter, C., Hemmerling, T. M., Lanchon, R., Valoti, E., Remy, A., Leuillet, S., & Ouattara, A. (2016). The feasibility of a completely automated total IV anesthesia drug delivery system for cardiac surgery. Anesthesia & Analgesia123(4), 885-893.

[8] Angie, D. (2018). 6 insights on how artificial intelligence could transform anesthesia. Becker’s ASC Review. Obtained from: https://www.beckersasc.com/anesthesia/6-insights-on-how-artificial-intelligence-could-transform-anesthesia.html

Mark David is a writer best known for his science fiction, but over the course of his life he published more than sixty books of fiction and non-fiction, including children's books, poetry, short stories, essays, and young-adult fiction. He publishes news on apstersmedia.com related to the science.

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Apple’s own 5G modem-equipped iPhone SE 4 is “confirmed” to launch in March

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Tom O’Malley, an analyst at Barclays, recently visited Asia with his colleagues to speak with suppliers and makers of electronics. The analysts said they had “confirmed” that a fourth-generation iPhone SE with an Apple-designed 5G modem is scheduled to launch near the end of the first quarter next year in a research note they released this week that outlines the main conclusions from the trip. That timeline implies that the next iPhone SE will be unveiled in March, similar to when the present model was unveiled in 2022, in keeping with earlier rumors.

The rumored features of the fourth-generation iPhone SE include a 6.1-inch OLED display, Face ID, a newer A-series chip, a USB-C port, a single 48-megapixel rear camera, 8GB of RAM to enable Apple Intelligence support, and the previously mentioned Apple-designed 5G modem. The SE is anticipated to have a similar design to the base iPhone 14.

Since 2018, Apple is said to have been developing its own 5G modem for iPhones, a move that will let it lessen and eventually do away with its reliance on Qualcomm. With Qualcomm’s 5G modem supply arrangement for iPhone launches extended through 2026 earlier this year, Apple still has plenty of time to finish switching to its own modem. In addition to the fourth-generation iPhone SE, Apple analyst Ming-Chi Kuo earlier stated that the so-called “iPhone 17 Air” would come with a 5G modem that was created by Apple.

Whether Apple’s initial 5G modem would offer any advantages to consumers over Qualcomm’s modems, such quicker speeds, is uncertain.

Qualcomm was sued by Apple in 2017 for anticompetitive behavior and $1 billion in unpaid royalties. In 2019, Apple purchased the majority of Intel’s smartphone modem business after the two firms reached a settlement in the dispute. Apple was able to support its development by acquiring a portfolio of patents relating to cellular technology. It appears that we will eventually be able to enjoy the results of our effort in four more months.

On March 8, 2022, Apple made the announcement of the third-generation iPhone SE online. With antiquated features like a Touch ID button, a Lightning port, and large bezels surrounding the screen, the handset resembles the iPhone 8. The iPhone SE presently retails for $429 in the United States, but the new model may see a price increase of at least a little.

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Google is said to be discontinuing the Pixel Tablet 2 and may be leaving the market once more

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Google terminated the development of the Pixel Tablet 3 yesterday, according to Android Headlines, even before a second-generation model was announced. The second-generation Pixel Tablet has actually been canceled, according to the report. This means that the gadget that was released last year will likely be a one-off, and Google is abandoning the tablet market for the second time in just over five years.

If accurate, the report indicates that Google has determined that it is not worth investing more money in a follow-up because of the dismal sales of the Pixel Tablet. Rumors of a keyboard accessory and more functionality for the now-defunct project surfaced as recently as last week.

It’s important to keep in mind that Google’s Nest subsidiary may abandon its plans for large-screen products in favor of developing technologies like the Nest Hub and Hub Max rather than standalone tablets.

Google has always had difficulty making a significant impact in the tablet market and creating a competitor that can match Apple’s iPad in terms of sales and general performance, not helped in the least by its inconsistent approach. Even though the hardware was good, it never really fought back after getting off to a promising start with the Nexus 7 eons ago. Another problem that has hampered Google’s efforts is that Android significantly trails iPadOS in terms of the quantity of third-party apps that are tablet-optimized.

After the Pixel Slate received tremendously unfavorable reviews, the firm first declared that it was finished producing tablets in 2019. Two tablets that were still in development at the time were discarded.

By 2022, however, Google had altered its mind and declared that a tablet was being developed by its Pixel hardware team. The $499 Pixel Tablet was the final version of the gadget, which came with a speaker dock that the tablet could magnetically connect to. (Google would subsequently charge $399 for the tablet alone.)

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Windows 11 PCs with Arm Processors now have an Official ISO for Clean Installations

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Power users occasionally prefer to start over when they acquire a new computer, so they follow the pro-gamers’ advice and reinstall Windows using a brand-new ISO image that comes straight from Microsoft and is free of bloatware and needlessly complex “driver management programs.” Up until recently, the new Snapdragon laptops’ more specialized version of Windows 11 didn’t support that.

The Windows 11 build on these new laptops is unusual because of the Arm64-based hardware, which differs from the typical x86 and x64 innards found in most laptops and desktops. Microsoft has finally released a disk image (or ISO file) for these devices after several months of waiting. To perform a direct reinstallation or make a bootable flash drive for a different device, you may now download it straight from Microsoft’s website. It is identical to the installation media utility that is currently available.

Be aware that there may be some glitches if you use this method for a fresh install. Compared to previous designs, the Snapdragon X system-on-a-chip has a lot fewer hardware variables, but because it’s so new, Windows Update might not include all the necessary components. You may need to use an Ethernet connection or the old-fashioned sneakernet to manually load drivers from another computer. You may also need to do some Googling to locate all the files you require for that.

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