When more than 23,000 adults across 31 countries were asked about the main problems in healthcare, most cited access to treatment and long waiting times.
They also mentioned issues such as insufficient staff, the cost of accessing treatment, lack of investment in preventive health, and an aging population.
There are many challenges in global healthcare systems. aI, along with companies like Google and Nvidia, is stepping in to help solve these problems quickly and efficiently.
What role does AI play in healthcare?
aI has become essential for automating time-consuming tasks quickly and efficiently, with minimal human involvement. This has been particularly beneficial for many healthcare businesses.
For example, aI tools have been transformative for the Lung Institute, especially following the COVID-19 pandemic.
Despite the healthcare industry’s preference for traditional methods, it’s important to explore aI tools. This can be a crucial first step in addressing gaps in the healthcare system.
another important use of AI in healthcare is in medical imaging.
analyzing medical images such as MRIs, CT scans, ultrasounds, and X-rays can take a human professional anywhere from a few minutes to several days, depending on the complexity.
However, aI algorithms can analyze these images quickly and accurately, leading to better patient outcomes.
This is why many healthcare businesses are now focusing on aI-assisted medical imaging. The market for this technology is expected to exceed $840 million by 2030. For more information on how AI is revolutionizing healthcare, watch this video.
Next, let’s consider personalized medicine.
No two human beings are genetically identical, not even identical twins. Each person’s unique genetic makeup, lifestyle choices, and healthcare needs require different medical treatments. Using the vast data AI is built on, this technology can analyze a patient’s medical history, family medical history, genetic information, and other essential factors. Optometry Medical Billing Services can predict disease risks and recommend treatments tailored to the patient’s specific needs and preferences.
For more insights on this topic, check out this blog on AI Product Design.
In a Forbes article, Renen Hallak, founder and CEO of VaST Data, believes AI will lead to the “democratization of personalized medicine.” “Personalized medicine shifts the practice from statistics, the law of averages, and hoping for the best outcome to more precisely identifying abnormalities within the individual patient,” Hallak writes. “Over the next several years, I believe we’ll reach a point where an individual’s health will be nearly pristine.”
Telemedicine uses telecommunication technology to provide healthcare services when distance is an issue. It can be as simple as asking a healthcare provider via text how much Tylenol a pregnant person can take in one day, or as advanced as performing an appendectomy through remote surgery, also known as telesurgery.
Integrating AI into healthcare can enhance diagnostic accuracy, remote patient monitoring, teleconsultations, and personalized care, leading to better patient outcomes.
Generative AI is also valuable in drug discovery and development, from identifying and validating targets to getting the drug to market. Traditional drug discovery relies on expensive and time-consuming trial and error, whereas AI-powered drug discovery is more cost-effective and faster.
On average, it takes ten years and $1.4 billion to bring a single drug from the lab to market. according to McKinsey, aI-assisted drug development can achieve the following:
- Up to 50% cost reduction
- a 12-month acceleration in trial time
- at least a 20% increase in net present value (NPV)
For more information on AI development, see here: https://linkupst.com/services/ai-development.
Now let’s talk about who’s driving this innovation.
Who are the key players in AI healthcare?
Many AI-powered companies are leading the healthcare revolution, applying AI to solve some of the field’s most challenging problems. Arterys uses imaging technology to simplify the diagnosis of heart defects in newborns and children. Google Health is developing AI models like Med-PaLM 2 for healthcare applications.
another AI-powered company, Butterfly Network, makes ultrasound scans more accessible to underserved communities with its handheld whole-body imager and AI image interpreter. Their work is quite impressive. On the backend, aI hardware manufacturers like Nvidia support these advancements.
Here’s some context.
Unlike central processing units (CPUs), which have powered computing for years, graphic processing units (GPUs) are now essential for AI. GPUs excel in complex mathematical computations and parallel processing, crucial for advanced technologies like AI.
as a result, the New York Times has called GPUs “AI Boom’s Most Indispensable Prize.
In his address, Huang described it as “a very big GPU.” according to a company press release, NVIDIa’s GB200 Grace Blackwell Superchip allows organizations to build and run real-time generative aI on trillion-parameter large language models at up to 25 times less cost and energy consumption than its predecessor.
This means that everything AI can do in healthcare will be done faster, at a lower cost, and with greater accuracy. “Blackwell’s breakthrough technological capabilities will provide the critical computing needed to help the world’s brightest minds chart new scientific discoveries,” said Demis Hassabis, co-founder and CEO of Google DeepMind, in the press release.
Concerns about aI in Healthcare
The major concerns about AI in healthcare are two-fold.
First, there’s confidentiality and patient data privacy. Most people consider their medical history extremely private. No one wants others to know about the medical issues they have faced.
Doctor-patient confidentiality exists to protect personal health information. However, aI models require vast amounts of data to function effectively, including diagnostic images, genetic information, and medical records.
This makes them a lucrative target for hackers. The Department of Health and Human Services (HHS) tracks healthcare data breaches affecting at least 500 individuals through a breach notification portal.
as of April 2024, nearly 250 breaches of healthcare data have already been reported on the HHS portal. The main cause is hacking, which remains a significant cyber threat in healthcare. With aI handling large amounts of data, confidential patient information can become an easy target.
The second concern is reliability.
according to a Pew Research report, 60% of American adults say they would feel uncomfortable if their healthcare provider used AI for diagnosing diseases and recommending treatments. This discomfort is understandable, given the concerns about the transparency and accountability of AI algorithms, as well as potential biases.
So, in response to the question, aI in healthcare does indeed show significant promise. However, achieving its full potential will require considerable effort and dedication. The integration of AI into healthcare systems can revolutionize patient care, improve diagnostic accuracy, and enhance personalized treatment plans. Yet, it also brings challenges that need to be addressed, such as ensuring data privacy, overcoming technical barriers, and fostering trust among healthcare professionals and patients.
For AI to reach its full potential in healthcare, there must be a collaborative effort among technology developers, healthcare providers, policymakers, and patients. This includes investing in robust data security measures to protect patient information, developing transparent AI algorithms to minimize bias, and providing ongoing education and training for healthcare professionals to effectively use aI tools.
As AI continues to evolve, organizations like Linkup Studio are at the forefront of developing innovative AI solutions tailored to the unique needs of the healthcare industry. By working together, we can harness the power of AI to create a more efficient, effective, and equitable healthcare system for all.
In summary, while the journey to fully realizing AI’s potential in healthcare is complex, the benefits it promises make the effort worthwhile. With continued investment, collaboration, and innovation, AI can transform healthcare into a more advanced and patient-centric field.