Will You Get Your Hearing Back? AI Has the Answer

FEATURED RESEARCH

Will You Get Your Hearing Back? AI Has the Answer

Sudden hearing loss can be unsettling. One moment, your hearing is fine, and the next, it’s significantly impaired. Determining who will regain their hearing and who won't has been a difficult task for doctors, but AI is now providing a clearer picture.

Traditional methods for predicting recovery from sudden sensorineural hearing loss (SSNHL) often rely on clinical markers and extensive lab tests, which aren’t always available or reliable.

Research from Hanyang University in Seoul developed a deep learning model to improve prediction accuracy. The researchers analyzed data from 1,108 SSNHL patients treated between 2015 and 2023.

Key findings: The AI model predicted complete hearing recovery with an accuracy of 89.2%, which outperformed traditional approaches.

It also demonstrated a 92.2% success rate in determining whether patients met Siegel’s criteria for complete recovery.

The model considered various factors, such as initial hearing thresholds, patient age, and the presence of symptoms like tinnitus and vertigo.

Why it matters: This AI model offers actionable insights that can lead to more personalized treatments.

For instance, patients with a pure tone threshold of 4000 Hz in the affected ear were identified as having a significant predictor of recovery.

With these findings, doctors can tailor treatments more precisely. Patients likely to recover may avoid unnecessary interventions, while those at risk could receive more targeted care earlier.

If AI can help us hear again, what other senses might it someday restore?

For more details: Full Article

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CANCER THERAPY

Noetik Secures $40 Million to Advance Cancer Therapies

Noetik, a biotech company using AI and advanced data to develop cancer treatments, has raised $40 million in a Series A financing round.

Polaris Partners led the round, with support from new and existing investors.

What Neotik does: Noetik focuses on creating a detailed atlas of human cancer biology using high-tech data and in vivo CRISPR technology.

This approach helps them identify new drug targets faster. By training AI models on this data, Noetik aims to speed up the discovery of new cancer treatments.

Why it matters: This funding will allow Noetik to expand its cancer biology atlas and improve its AI-driven discovery tools.

The goal is to develop more effective cancer treatments and get them to patients more quickly. Noetik also plans to team up with academic institutions, healthcare providers, and pharmaceutical companies to further its work.

The recent addition of Dr. Shafique Virani as Chief Business Officer shows their commitment to growing their impact in cancer treatment.

For more details: Full Press Release

💰 3 Other funded companies

1. Melodi Health raised $10.75 million in Series A funding to enhance its breast reconstruction technologies, including the Melodi Matrix bioabsorbable mesh, and to support the "ARIA" trial aimed at FDA approval. [Link]

2. eXeX, a med tech company specializing in AI and spatial computing for surgical optimization, raised $5.8 million in seed funding to accelerate platform development ahead of its commercial launch in early 2025. [Link]

3. Slingshot AI raised about $30 million in seed funding led by Andreessen Horowitz to advance its AI-driven mental health solutions and expand global partnerships with mental health providers. [Link]

New Partnerships

HEART DISEASE

BridgeBio Partners to Tackle Hidden Heart Disease with AI

BridgeBio Pharma is teaming up with the CarDS Lab at Yale School of Medicine to improve the diagnosis of Transthyretin Amyloid Cardiomyopathy (ATTR-CM), a heart disease that’s often missed.

Together, they’re using advanced AI tools to catch the condition earlier, especially in diverse patient groups across the U.S.

The TRACE-AI network Study: This partnership focuses on the TRACE-AI Network Study, which will scan large health system records using AI to find undiagnosed cases of ATTR-CM.

The study also aims to figure out how common the disease is in people without symptoms and track its progression in high-risk patients.

Why it matters: ATTR-CM is tough to diagnose because its symptoms often look like other heart issues. The study uses AI to analyze data from electrocardiograms and ultrasounds to catch the disease earlier.

Jennifer Hodge from BridgeBio says this effort is about making advanced testing more accessible and effective, especially for groups that are often overlooked.

Dr. Rohan Khera from the CarDS Lab points out that this is the first large-scale AI effort aimed at fixing underdiagnosis in diverse health systems.

The AI tools they’re developing are designed to work with data already available in clinics, making it easier to use across different healthcare settings.

For more details: Full Press Release

🤝 2 Other collaborations shaping the future

1. Qventus has partnered with Northwestern Medicine to implement an AI-powered operational assistant that helps patients better prepare for surgeries by automating pre-surgical planning and coordination. [Link]

2. SoundHound AI partnered with MUSC Health to introduce "Emily," an AI agent that enhances patient appointment management by streamlining scheduling and non-clinical inquiries, leveraging integration with Epic to boost efficiency and patient satisfaction. [Link]

Milestone Moments

⚡1 Product launches, 1 acquisition, 3 regulatory approval

1. GE HealthCare introduced its AI-enhanced cardiology solutions for real-time cardiac assessments and ECG-less Cardiac CT at ESC 2024, aiming to improve diagnostic speed and accuracy at the point of care. [Link]

2. Arsenal Capital Partners acquired Knowtion Health to bolster its portfolio in healthcare technology, particularly in AI-driven clinical and revenue solutions. [Link]

3. Qure.ai received FDA clearance for its AI-powered tool designed to analyze lung nodules on CT scans, enhancing early detection and diagnosis of potential lung cancer. [Link]

4. Augere Medical received MDR CE-mark approval for its PolypAId™ System, an AI-powered tool to enhance polyp detection during colonoscopies, allowing for its European launch and aiming to improve early colorectal cancer detection. [Link]

5. PathAI's AISight Dx Image Management System received CE Mark certification for primary diagnosis in Europe, enhancing AI-driven pathology workflows and expanding its market presence in anatomic pathology labs. [Link]

Opinion and Perspectives

AI IN HEALTHCARE

The AI Chasm: Why Doctors Aren’t Ready to Trust the Tech Yet

AI is making waves in medicine, but there’s a gap between its potential and practical use in clinics. Researchers from the University of Adelaide call this the “AI chasm,” and it’s a problem we can’t ignore.

The AI chasm: AI can analyze huge amounts of data quickly, but it lacks the context that human clinicians bring to the table.

Clinicians use sensory cues, like the brightness of a nodule on a mammogram, to guide their decisions. These cues aren’t something AI can fully grasp yet.

As Lana Tikhomirov, a Ph.D. student involved in the research, points out, “Misconceptions about AI restrict our ability to maximize this new technology.”

Why it matters: This mismatch between AI and human decision-making leads to issues like “automation bias,” where doctors might rely too much on AI or, on the flip side, not trust it enough.

AI doesn’t have the ability to question its data like a human would, which is a crucial part of making accurate diagnoses.

To bridge this gap, we need to treat AI like a clinical drug—evaluating its effects on decision-making and ensuring it supports, not replaces, human expertise.

The future of AI in medicine depends on how well we navigate this chasm, making AI a true partner in healthcare.

For more details: Full Article

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