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"Psychiatric care should be accessible like a cold: when symptoms appear, patients should be able to visit immediately for diagnosis and treatment. Lysorus aims to create psychiatric clinics that are fast, affordable, and deliver excellent treatment outcomes."
This is the vision of the hospital envisioned by Bae Sang-yun (CEO), CEO of medical AI startup Lysorus. Lysorus is developing an AI solution that analyzes electroencephalogram (EEG) data to diagnose psychiatric and neurological disorders such as epilepsy and sleep disturbances, while also predicting individual patient responses to medications. With the goal of establishing a psychiatric and neurological care system that is cheaper, faster, and more effective than existing models, the company is currently preparing to enter the U.S. market.
When Bae (CEO), then a student at Seoul National University College of Medicine, launched the startup, he chose psychiatry among various medical fields based on the judgment that it would yield the greatest impact when combined with AI.
Bae (CEO) explained, "In cancer surgery, highly skilled surgeons are essential. Unless autonomous robotic surgery that replicates human dexterity and expertise emerges, even with AI adoption, its effectiveness will inevitably be limited." He added, "However, psychiatry is different. Since counseling and medication prescription are the core components, the potential impact of adding AI-based precise judgment is significant."
Typically, psychiatric diagnoses can vary depending on a patient's subjective statements and communication abilities. In contrast, brainwave data provides objective clues about a patient's condition. For instance, even if a patient forces a smile to conceal depression, their brainwaves cannot easily hide this state. This perspective is embedded in the company name Lysorus. 'Lysorius' refers to the zygomaticus major muscle, which activates when people force a smile. The name reflects the idea that while humans can deceive, data cannot be easily falsified.
The company does not stop at improving diagnostic accuracy through brainwave data analysis. Bae (CEO) stated, "Diagnosis ultimately serves to enable precise treatment," and added, "Our primary focus is on developing solutions that predict drug responses to identify the most effective treatment methods."
Historically, prescribing psychiatric medications has involved numerous inefficiencies. For example, if Drug A proves ineffective or causes side effects, physicians switch to Drug B.
Bae (CEO) explained, "Lysorus aims to leverage AI to minimize such trial-and-error from the outset, helping prescribe medications that offer the best efficacy with minimal side effects for each patient."
Lysorus's mid-to-long-term vision is the establishment of psychiatry clinics powered by AI infrastructure. When patients arrive at a hospital for treatment, AI will conduct initial assessments and analyze brainwave data collected via wearable devices. Based on this analysis, AI will generate reports, which physicians will then reference to finalize medication prescriptions.
The plan is not to rely solely on AI judgment but to create a clinical and therapeutic system that integrates brainwave data with physician expertise. Currently, the company is rapidly accumulating data through proof-of-concept (PoC) collaborations with domestic hospitals and Vietnamese hospitals, enhancing the accuracy of its drug response prediction AI solution. Additionally, discussions are underway regarding potential partnerships with major corporations such as Samsung Electronics to further advance its proprietary wearable device for brainwave collection.
U.S. Low-Income Patient Care: A Market Ignored by Physicians… AI Can Enable Profitability
Lysorus is initially targeting the U.S. healthcare vulnerable population. In the United States, mental health issues such as substance abuse are often intertwined among low-income groups, accompanied by multiple other health complications.
However, psychiatric treatment in the U.S. is largely perceived as exclusive to high-income patients. Counseling typically requires around one hour and incurs high costs, making it difficult for low-income individuals to afford. Furthermore, public insurance programs like Medicaid, which this demographic primarily uses, offer low reimbursement rates to hospitals, discouraging healthcare providers from actively pursuing this market.
Bae (CEO) described this as "a market abandoned simply because it is not profitable." Unlike competitors, Lysorus plans to aggressively target this segment. He stated, "By reducing physician dependency through an AI- and test-based system and lowering hospital operational costs, we believe profitability can be achieved even at low reimbursement rates." This approach allows the company to contribute to society while securing sufficient financial returns.
Bae (CEO) cited the significantly larger size of the U.S. medical AI market compared to South Korea's, along with greater accessibility, as key reasons for focusing intensively on the United States. In South Korea, various constraints make operating AI-driven hospitals challenging. Conversely, in the U.S., major hospital systems such as Mayo Clinic, Cleveland Clinic, Mount Sinai, and Kaiser Permanente are already actively utilizing AI for clinical support, documentation, image interpretation, and clinical trial matching.
To move one step closer to Lysorus's ultimate vision, Bae (CEO) aims to establish a U.S. subsidiary within this year. Bae (CEO) said, "Ultimately, we want to build a system that does not overly rely on individual medical professionals, enabling low-income individuals to benefit from mental health treatment," and added, "We aspire to create an era where psychiatric care can be treated as easily as a cold—simply 'click' and resolved."
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