Category: 3. Business

Microsoft has revealed details of an artificial intelligence system that performs better than human doctors at complex health diagnoses, creating a “path to medical superintelligence”.

The company’s AI unit, which is led by the British tech pioneer Mustafa Suleyman, has developed a system that imitates a panel of expert physicians tackling “diagnostically complex and intellectually demanding” cases.

Microsoft said that when paired with OpenAI’s advanced o3 AI model, its approach “solved” more than eight of 10 case studies specially chosen for the diagnostic challenge. When those case studies were tried on practising physicians – who had no access to colleagues, textbooks or chatbots – the accuracy rate was two out of 10.

Microsoft said it was also a cheaper option than using human doctors because it was more efficient at ordering tests.

Despite highlighting the potential cost savings from its research, Microsoft played down the job implications, saying it believed AI would complement doctors’ roles rather than replace them.

“Their clinical roles are much broader than simply making a diagnosis. They need to navigate ambiguity and build trust with patients and their families in a way that AI isn’t set up to do,” the company wrote in a blogpost announcing the research, which is being submitted for peer review.

However, using the slogan “path to medical superintelligence” raises the prospect of radical change in the healthcare market. While artificial general intelligence (AGI) refers to systems that match human cognitive abilities at any given task, superintelligence is an equally theoretical term referring to a system that exceeds human intellectual performance across the board.

Suleyman, the chief executive of Microsoft AI, told the Guardian the system would be operating perfectly within the next decade.

“It’s pretty clear that we are on a path to these systems getting almost error-free in the next 5-10 years. It will be a massive weight off the shoulders of all health systems around the world,” he said.

Explaining the rationale behind the research, Microsoft raised doubt over AI’s ability to score exceptionally well in the United States Medical Licensing Examination, a key test for obtaining a medical licence in the US. It said the multiple-choice tests favoured memorising answers over deep understanding of a subject, which could help “overstate” the competence of an AI model.

Microsoft said it was developing a system that, like a real-world clinician, takes step-by-step measures – such as asking specific questions and requesting diagnostic tests – to arrive at a final diagnosis. For instance, a patient with symptoms of a cough and fever may require blood tests and a chest X-ray before the doctor arrives at a diagnosis of pneumonia.

The new Microsoft approach uses complex case studies from the New England Journal of Medicine (NEJM).

Suleyman’s team transformed more than 300 of these studies into “interactive case challenges” that it used to test its approach. Microsoft’s approach used existing AI models, including those produced by ChatGPT’s developer, OpenAI, Mark Zuckerberg’s Meta, Anthropic, Elon Musk’s Grok and Google’s Gemini.

Microsoft then used a bespoke, agent-like AI system called a “diagnostic orchestrator” to work with a given model on what tests to order and what the diagnosis might be. The orchestrator in effect imitates a panel of physicians, which then comes up with the diagnosis.

Microsoft said that when paired with OpenAI’s advanced o3 model, it “solved” more than eight of 10 NEJM case studies – compared with a two out of 10 success rate for human doctors.

Microsoft said its approach was able to wield a “breadth and depth of expertise” that went beyond individual physicians because it could span multiple medical disciplines.

It added: “Scaling this level of reasoning – and beyond – has the potential to reshape healthcare. AI could empower patients to self-manage routine aspects of care and equip clinicians with advanced decision support for complex cases.”

Microsoft acknowledged its work is not ready for clinical use. Further testing is needed on its “orchestrator” to assess its performance on more common symptoms, for instance.

By Greg Robb

Treasury Secretary says Fed seems ‘frozen at the wheel’

President Donald Trump has continued to put pressure on Federal Reserve Chair Jerome Powell to dramatically lower interest rates.

At a Monday press briefing, White House Press Secretary Karoline Leavitt held up a handwritten note to the Fed leader from the president.

The letter suggested that Trump thinks the Fed’s benchmark rate should be between close to 0.5%, down from its current range of 4.25% to 4.5%.

The note read: “Jerome, You are, as usual, ‘too late.’ You have cost the USA a fortune – and continue to do so – You should lower the rate – by a lot. Hundreds of billions of dollars being lost. No Inflation”

Powell has been pushing back on rate cuts all year, saying he wants to wait to learn more about “the likely course of the economy” from the president’s tariff policy.

The Fed will meet again in July to consider a rate cut. The market is pricing in only about a 20% chance of a cut at that meeting, after a key inflation measure released last week was slightly hotter than expected.

Traders are now pricing in three quarter-point cuts at the Fed’s final three meetings of the year, starting in September. Analysts at JPMorgan say the reasons behind the cuts may not be supportive for stocks.

Earlier Monday, other top White House officials also kept up the criticism of Powell.

Treasury Secretary Scott Bessent said in a Bloomberg interview that Fed officials “seem a little frozen at the wheel.”

Bessent said the Fed was too worried about making another mistake like its failure to see high inflation brewing in 2022.

Powell’s term as Fed chair ends next May. In the interview, Bessent said the White House will be working “over coming weeks and months” on choosing Powell’s successor.

Additionally, Fed Governor Adriana Kugler’s term at the central bank is up at the end of January. Bessent said the White House might use the vacancy created by Kugler’s departure to put Powell’s replacement on the Fed’s seven-member board of governors.

Bessent is considered to be on the short list of possible replacements for Powell.

Asked about this possibility, Bessent said: “I will do what the president wants, but I think I have the best job in D.C.”

-Greg Robb

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As treatment approaches in multiple myeloma continue to advance, new areas of controversy arise, leading to undefined expectations within clinical practice, according to Ajai Chari, MD.

Accordingly, experts gathered at the inaugural Bridging the Gaps in Leukemia, Lymphoma, and Multiple Myeloma Conference to identify current controversies or challenges in the field and come to a consensus about the optimal approaches to myeloma management. An overview of these findings was published in a manuscript after the meeting.

“There’s a joke in that if you ask myeloma doctors for an opinion, you’ll get 6 answers. This [meeting] shows that there’s a lot of complexity and evolving data [in the multiple myeloma space],” Ajai Chari, MD, explained in an interview with OncLive®.

During the interview, Chari detailed the importance of publishing this manuscript; the limitations to current risk stratification approaches in smoldering multiple myeloma; ongoing challenges regarding determination of the optimal timing for treatment initiation; and what the potential FDA approval of daratumumab (Darzalex) could mean for this patient population.

Chari is director of the Multiple Myeloma Program and a professor of medicine in the School of Medicine at the University of California, San Francisco.

OncLive: What is the importance of publishing this manuscript from the Bridging the Gaps in Leukemia, Lymphoma, and Multiple Myeloma?

Chari: The purpose of this manuscript is to put a bunch of experts in the room and see how people think, where we agree, and where the areas of controversy are that we need to work on. It’s really for people who may not be doing this day in and day out, [in which we] take a little look under the hood, [so to speak].

How is risk stratification approached for smoldering multiple myeloma? Are there any limitations to current models?

Conventionally, risk stratification for smoldering has been based on static models. For example, how much M-spike [is present]? What’s the light chain? What’s the bone marrow burden? What are the immunoglobulin levels? The limitation there is that the date of diagnosis of smoldering myeloma is typically the date of the marrow, but somebody could have been smoldering prior to the marrow for anywhere from a month or 2 years. When you try to figure out who’s going to progress in the short term, that’s a big confounding variable. Although we need static models, because they’re convenient, we need more dynamic models, which tell us how the tumor is evolving. Are the protein levels going up? Is the hemoglobin drifting down? Are the bone lesions evolving? Those are where the field needs to go. Also, incorporating genetics, immune markers, and genomic markers. We haven’t gotten there yet, and that’s the struggle of serious stratification.

What are some key considerations when deciding on an optimal time to initiate therapy and treatment strategies in smoldering multiple myeloma?

The struggle with treating patients with smoldering myeloma is that they are essentially healthy people. They don’t have active myeloma. [The important questions are:] how do you not over-treat these patients with potentially toxic therapies that could cause adverse effects to help the individuals? Also, how do we not under-treat these patients? If we have amazing therapies that can help prevent symptoms and the onset of myeloma, shouldn’t we be doing that? That’s the tightrope that we have to walk in figuring out what the right time to initiate is. That’s where the risk stratification can help us make that decision.

What would the FDA approval of daratumumab mean for this space?

[Data from] the [phase 3] AQUILA study [NCT03301220] published in The New England Journal of Medicine showed, in a randomized fashion, that observation vs treatment with daratumumab…led to improved response, including progression-free survival and, surprisingly, overall survival. We just heard that the European Medical Association voted favorably on it; if that’s FDA approved, we could give patients with smoldering myeloma a relatively well-tolerated therapy, [particularly those who] we are concerned about progressing.

[Nevertheless], I’m most excited [to potentially use daratumumab plus lenalidomide [Revlimid], bortezomib [Velcade], and dexamethasone [Dara-VRd] for older patients who have smoldering myeloma and may have a high risk of progression. [These patients likely] would not be excited about having to receive a multidrug therapy in the future. [Therefore], it’s very reasonable to consider this

[Daratumumab] is a monoclonal antibody to help prevent the development of myeloma and potentially confer those clinical benefits. The challenge is that the study included 3 years of therapy, and that’s a [relatively] long period. Where I struggled more is with the younger patients; where they are now, they could easily tolerate multidrug therapy. However, do we need to commit everybody to 3 years of preventative therapy? This is another tightrope we have to walk.

Reference

Chari A, Bal S, Ailawadhi S, et al. Expert Perspectives on Current Challenges and Emerging Approaches for Multiple Myeloma: Narrative Review of an Inaugural Bridging the Gaps in Leukemia, Lymphoma, and Multiple Myeloma. Clin Lymphoma Myeloma Leuk. Published online March 11, 2025. doi:10.1016/j.clml.2025.03.008

Dear faculty and staff,

The next Circles of Excellence, on Aug. 7, will focus on how to increase your email marketing response rates and better understand your target audience.

Discover 5 strategies to increase your email marketing response rates

Ready to boost your email engagement? In this virtual presentation led by Strategic Marketing and Communications, we’ll explore five proven strategies to increase response rates in your email marketing and communications.

Backed by real-life examples and UIC-specific data, this session will highlight actionable tactics you can start using right away — including A/B testing, audience segmentation, personalized messaging and data-driven decision-making — all within UIC’s official Emma Email Marketing platform.

When:
1-2:30 p.m. Thursday, Aug. 7

Where:
Virtual via Zoom
Advance registration is required.

Who should attend:
Anyone who creates and sends email marketing campaigns using UIC’s Emma email marketing platform.

For questions or more information, please email smcs@uic.edu.

Together, let’s continue to elevate the transformational story of UIC, where access is broad and excellence thrives.

Gratefully,
Chandra Harris-McCray, PhD
Vice Chancellor for Strategic Marketing and Communications

For more information, please contact:
Strategic Marketing and Communications
smcs@uic.edu

Routine echocardiographic surveillance in adults with muscular dystrophy may uncover early signs of left ventricular systolic dysfunction (LVSD) and prompt timely intervention, but physical limitations can make consistent monitoring a challenge. Artificial intelligence (AI)–based electrocardiogram interpretation (AI-ECG) could offer a noninvasive, accessible alternative to routine echocardiography, according to findings published in the Journal of the American Society of Echocardiography.¹

“Our findings have potential implications for clinical practice. Current guidelines recommend routine echocardiographic monitoring for muscular dystrophy patients, typically on an annual or biannual basis,” the authors wrote. “However, obtaining high-quality echocardiographic images can be challenging due to patient-specific factors such as scoliosis and muscle weakness. Our findings suggest that AI-ECG could serve as a complementary screening tool, potentially allowing for more flexible and patient-friendly monitoring strategies.”

Cardiac complications are substantial contributors to mortality in muscular dystrophies, including Duchenne muscular dystrophy (DMD), in which up to 70% of patients experience LVSD.² Despite the recommendations for regular electrocardiography, capturing high-quality echocardiographic images can be challenging for patients with muscular dystrophy due to scoliosis, muscle weakness, immobility, and other physical limitations, the authors noted.¹

“Given these limitations and the current pressure on echocardiography availability in our health care systems, alternative methods for LVSD risk stratification are urgently needed,” the authors wrote. “[AI] applied to [AI-ECG] has shown promise for predicting LVSD in various populations. An ECG is widely accessible, cost-effective, and quick to perform (also in immobile populations), with the potential for home monitoring applications.”

The researchers identified patients with DMD, Becker muscular dystrophy, limb-girdle muscular dystrophy, or myotonic dystrophy who were 16 years or older and underwent an ECG and transthoracic echocardiogram within 90 days of each other at the University Medical Center Utrecht hospital in the Netherlands between 2007 and 2023. The data pool also included female carriers of DMD or BMD, who are also at a higher risk of cardiac complications.

A convolutional neural network was first trained using a derivation cohort of 53,874 ECG-echocardiogram pairs from 30,978 patients without muscular dystrophy to detect LVSD, then it was tested on a set of 390 ECG-echo pairs from 390 patients with muscular dystrophy. The researchers used a Cox proportional hazards model to determine the predictive value of AI-ECG for new-onset LVSD.

Follow-up echocardiography was available for 177 patients without LVSD at baseline. At a median follow-up of 4.8 (IQR, 2.6-8.6) years, LVSD occurred in 92 (52%) patients. LVSD prevalence ranged from 13.4% in patients with myotonic dystrophy to 81.3% in patients with DMD. No BMD female carriers showed LVSD, but 17.4% of DMD carriers had LVSD.

In the validation set, the model achieved an area under the receiving operator curve (AUROC) of 0.86 (95% CI, 0.85-0.88), sensitivity of 0.90 (95% CI, 0.88-0.92), and specificity of 0.58 (95% CI, 0.56-0.60). In the muscular dystrophy test set, the model demonstrated an AUROC of 0.83 (95% CI, 0.79-0.87), sensitivity of 0.87 (95% CI, 0.81–0.93), and specificity of 0.58 (95% CI, 0.52-0.63). The negative predictive value was 0.91 (95% CI, 0.86-0.95), and the positive predictive value was 0.49 (95% CI, 0.43-0.53).

The model overall showed an AUROC of 0.72 (95% CI, 0.66-0.78) for predicting new-onset LVSD, and the AI-ECG probability was a significant predictor of LVSD occurrence.

Despite the model’s potential, the authors cautioned that timely diagnosis of LVSD and initiation of cardioprotective treatment are crucial. Therefore, AI-ECG must be evaluated in a structured clinical framework to ensure that it improves established monitoring methods rather than replaces them. The clinical utility, cost-effectiveness, and optimal integration of AI-ECG into current care standards must also be determined through prospective studies and cluster randomized trials, they added. Their study was also limited by its single-center nature and reliance on routine clinical interpretation of echocardiograms.

“This study demonstrates that AI-ECG can accurately detect and predict LVSD in muscular dystrophy patients, offering a non-invasive, widely accessible, and applicable tool for cardiac risk stratification,” the authors concluded. “The ability to detect and predict LVSD may enable more personalized follow-up strategies, reducing reliance on echocardiography. Future research should focus on external validation and pediatric application.”

References

1. Arends BKO, Zwetsloot PM, Heeres PS, et al. Left ventricular systolic dysfunction screening in muscular dystrophies using deep learning-based electrocardiogram interpretation. J Electrocardiol. Published online June 12, 2025. doi:10.1016/j.jelectrocard.2025.154048

2. Verhaert D, Richards K, Rafael-Fortney JA, Raman SV. Cardiac involvement in patients with muscular dystrophies: magnetic resonance imaging phenotype and genotypic considerations. Circ Cardiovasc Imaging. 2011;4(1):67-76. doi:10.1161/CIRCIMAGING.110.960740

BEIJING, June 30, 2025 (GLOBE NEWSWIRE) — TIAN RUIXIANG Holdings Ltd (Nasdaq: TIRX) (the “Company” or “TRX”), a China-based insurance broker, today announced it has completed the acquisition of 100% of issued and outstanding shares of Ucare Inc. (“Ucare”), the sole operator of China’s only cloud-based AI-driven hospital and health insurance risk management platform. The all-stock transaction, valued at US$150 million, marks a major milestone in TRX’s strategy to expand into in-hospital distribution channels and capture new growth opportunities within the health insurance sector.

As part of the closing, TRX has issued 101,486,575 Class A ordinary shares, each with a par value of US$0.025. Powered by the largest hospital database and a cloud-based generative AI platform, Ucare develops innovative healthcare solutions that help providers, payers, and institutions reduce fraud, abuse, waste, and administrative costs. Following the acquisition, Ucare will harness TRX’s robust platform, capital resources, and strategic relationships to advance R&D, embed cutting-edge generative AI into clinical pathways, and broaden its reach from healthcare providers to insurance partners.

Leveraging Ucare’s existing relationships with over 4,000 hospitals and leading AI analytics, TRX will expand business channels and build unique health insurance service offerings. Ucare’s generative AI platform will be integrated into TRX’s underwriting and claims processing health insurance workflows to reduce fraud, streamline operations, and improve pricing precision.

Ms. Sheng Xu, Director, Chairwoman and Chief Executive Officer of TRX, stated, “We are thrilled to officially welcome Ucare to the TRX family. This acquisition places us at the intersection of healthcare and insurance, unlocking data-driven insights that will transform how health insurance is designed, sold, and serviced. In the coming months, we are focused on expediting Ucare’s growth by building on the success it’s already achieved, while designing differentiated offerings that align with evolving patient needs and national healthcare priorities. Our long-term goal is to create a seamless insurance-hospital ecosystem that enhances transparency, efficiency, and accessibility for all stakeholders.”

Mr. Wei Zhu, Chief Executive Officer of Ucare, added, “Joining TRX opens an exciting new chapter for Ucare’s mission to reshape hospital and health insurance risk management in China. With TRX’s resources, we are well-positioned to accelerate our platform deployment and deepen integration with insurance services. Together, we will lead the next wave of innovation in medical cost containment and health insurance.”

About TIAN RUIXIANG Holdings Ltd
TIAN RUIXIANG Holdings Ltd, headquartered in Beijing, China, is an insurance broker operating in China through its China-based variable interest entity. It distributes a wide range of insurance products, which are categorized into two major groups: (1) property and casualty insurance, such as commercial property insurance, liability insurance, accidental insurance, and automobile insurance; and (2) other types of insurance, such as health insurance, life insurance, and other miscellaneous insurance.

About Ucare Inc.
Ucare Inc. develops innovative healthcare solutions that enable providers, payers, and institutions to reduce fraud, abuse, waste, and administrative costs. Powered by the largest hospital database, Ucare’s cloud-based generative AI platform continuously refines disease models by integrating real-world data, the latest medical guidelines, and real-time intelligence. Ucare’s vision is to ease the burden on patients, expand coverage, and ultimately improve access to healthcare for everyone.

Forward-Looking Statements
Certain statements in this announcement are forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties and are based on current expectations and projections about future events and financial trends that the Company believes may affect its financial condition, results of operations, business strategy and financial needs. Investors can identify these forward-looking statements by words or phrases such as “may,” “will,” “expect,” “anticipate,” “aim,” “estimate,” “intend,” “plan,” “believe,” “potential,” “continue,” “is/are likely to” or other similar expressions. The Company undertakes no obligation to update forward-looking statements to reflect subsequent occurring events or circumstances, or changes in its expectations, except as may be required by law. Although the Company believes that the expectations expressed in these forward-looking statements are reasonable, it cannot assure you that such expectations will turn out to be correct, and the Company cautions investors that actual results may differ materially from the anticipated results and encourages investors to review risk factors that may affect its future results in the Company’s registration statement and in its other filings with the U.S. Securities and Exchange Commission.

For investor and media enquiries, please contact:
TIAN RUIXIANG Holdings Ltd
Investor Relations Department
Email: ir@tianrx.com

Water Tower Research
Feifei Shen
Email: feifei@watertowerresearch.com