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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 has revealed a revamped Mac Mini with an M4 chip

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A smaller but no less powerful Mac Mini was recently unveiled by Apple as part of the company’s week of Mac-focused announcements. It now has Apple’s most recent M4 silicon, enables ray tracing for the first time, and comes pre-installed with 16GB of RAM, which seems to be the new standard in the age of Apple Intelligence. While the more potent M4 Pro model starts at $1,399, the machine still starts at $599 with the standard M4 CPU. The Mac Mini is available for preorder right now and will be in stores on November 8th, just like the updated iMac that was revealed yesterday.

The new design will be the first thing you notice. The Mini has reportedly been significantly reduced in size, although it was already a comparatively small desktop computer. It is now incredibly small, with dimensions of five inches for both length and width. Apple claims that “an innovative thermal architecture, which guides air to different levels of the system, while all venting is done through the foot” and the M4’s efficiency are the reasons it keeps things cool.

Nevertheless, Apple has packed this device with a ton of input/output, including a 3.5mm audio jack and two USB-C connections on the front. Three USB-C/Thunderbolt ports, Ethernet, and HDMI are located around the back. Although the USB-A ports are outdated, it’s important to remember that the base M2 Mini only featured two USB-A connectors and two Thunderbolt 4 ports. You get a total of five ports with the M4. You get an additional Thunderbolt port but lose native USB-A.

Depending on the M4 processor you select, those Thunderbolt connectors will have varying speeds. While the M4 Pro offers the most recent Thunderbolt 5 throughput, the standard M4 processor comes with Thunderbolt 4.

With its 14 CPU and 20 GPU cores, the M4 Pro Mac Mini also offers better overall performance. The standard M4 can have up to 32GB of RAM, while the M4 Pro can have up to 64GB. The maximum storage capacity is an astounding 8TB. Therefore, even though the Mini is rather little, if you have the money, you can make it really powerful. For those who desire it, 10 gigabit Ethernet is still an optional upgrade.

Apple has a big week ahead of it. On Monday, the company released the M4 iMac and its first Apple Intelligence software features for iOS, iPadOS, and macOS. (More AI functionality will be available in December, such as ChatGPT integration and image production.) As Apple completes its new hardware, those updated MacBook Pros might make their appearance tomorrow. The business will undoubtedly highlight its newest fleet of Macs when it releases its quarterly profits on Thursday.

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Apple Intelligence may face competition from a new Qualcomm processor

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The new chip from Qualcomm (QCOM) may increase competition between Apple’s (AAPL) iOS and Android.

During its Snapdragon Summit on Monday, the firm unveiled the Snapdragon 8 Elite Mobile Platform, which includes a new, second-generation Oryon CPU that it claims is the “fastest mobile CPU in the world.” According to Qualcomm, multimodal generative artificial intelligence characteristics can be supported by the upcoming Snapdragon platform.

Qualcomm, which primarily creates chips for mobile devices running Android, claims that the new Oryon CPU is 44% more power efficient and 45% faster. As the iPhone manufacturer releases its Apple Intelligence capabilities, the new Snapdragon 8 platform may allow smartphone firms compete with Apple on the AI frontier. Additionally, Apple has an agreement with OpenAI, the company that makes ChatGPT, to incorporate ChatGPT-4o into the upcoming iOS 18, iPadOS 18, and macOS Sequoia.

According to a September Wall Street Journal (NWSA) story, Qualcomm is apparently interested in purchasing Intel (INTC) in a deal that could be valued up to $90 billion. According to Bloomberg, Apollo Global Management (APO), an alternative asset manager, had also proposed an equity-like investment in Intel with a potential value of up to $5 billion.

According to reports, which cited anonymous sources familiar with the situation, Qualcomm may postpone its decision to acquire Intel until after the U.S. presidential election next month. According to the persons who spoke with Bloomberg, Qualcomm is waiting to make a decision on the transaction because of the possible effects on antitrust laws and tensions with China after the election results.

According to a report from analysts at Bank of America Global Research (BAC), Qualcomm could expand, take the lead in the market for core processor units, or CPUs, for servers, PCs, and mobile devices, and get access to Intel’s extensive chip fabrication facilities by acquiring Intel. They went on to say that Qualcomm would become the world’s largest semiconductor company if its $33 billion in chip revenue were combined with Intel’s $52 billion.

The experts claimed that those advantages would be outweighed by the financial and regulatory obstacles posed by a possible transaction. They are dubious about a prospective takeover and think that Intel’s competitors may gain from the ambiguity surrounding the agreement.

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iPhone 16 Pro Users Report Screen Responsiveness Issues, Hope for Software Fix

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Many iPhone 16 Pro and iPhone 16 Pro Max users are experiencing significant touchscreen responsiveness problems. Complaints about lagging screens and unresponsive taps and swipes are particularly frustrating for customers who have invested $999 and up in these devices.

The good news is that initial assessments suggest the issue may be software-related rather than a hardware defect. This means that Apple likely won’t need to issue recalls or replacement units; instead, a simple software update could resolve the problem.

The root of the issue might lie in the iOS touch rejection algorithm, which is designed to prevent accidental touches. If this feature is overly sensitive, it could ignore intentional inputs, especially when users’ fingers are near the new Camera Control on the right side of the display. Some users have reported that their intended touches are being dismissed, particularly when their fingers are close to this area.

Additionally, the new, thinner bezels on the iPhone 16 Pro compared to the iPhone 15 Pro could contribute to the problem. With less protection against accidental touches, the device may misinterpret valid taps as mistakes, leading to ignored inputs.

This isn’t the first time Apple has faced challenges with new iPhone models. For instance, the iPhone 4 experienced “Antennagate,” where signal loss occurred depending on how the device was held, prompting Steve Jobs to famously suggest users hold their phones differently. Apple eventually provided free rubber bumpers to mitigate the issue.

To alleviate the touchscreen problem, using a case might help by covering parts of the display and reducing the chances of accidental touches triggering the rejection algorithm. The issue appears on devices running iOS 18 and the iOS 18.1 beta and does not occur when the phone is locked. Users may notice difficulties when swiping through home screens and apps.

Many are hopeful that an upcoming iOS 18 update will address these issues, restoring responsiveness to the iPhone 16 Pro and iPhone 16 Pro Max displays.

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