How Hospitals Are Turning to AI to Win the Race Against Time

News

1. How Hospitals Are Turning to AI to Win the Race Against Time

2. Blackstone Leads $600 Million Funding Round in AI Cloud Startup Neysa

3. When AI Ambitions Meet the Geopolitics of Compute

4. AI Governance Debate Sharpens at Impact Summit

5. AI Policy Debate Turns to Power and Enforcement

6. India AI Summit Flags Urgent Reset in Skills Model

Cancer care is turning into a race against the clock that hospitals are trying to win with software, clinicians said in a panel discussion at the India AI Impact Summit 2026, describing AI systems that speed diagnosis, tailor treatment and reduce administrative drag.

Across two sessions—’AI for Societal Value: Responsible Innovation Across Healthcare,’ and ‘High-Impact Sectors and Innovation to Impact: AI as a Public Health Gamechanger,’—doctors and policymakers described how AI is already embedded in fertility labs, oncology departments, cardiac units and hospital operations. 

The debate, they suggested, has moved from adoption to accountability: How do we scale responsibly? How do we protect public trust? And how do we ensure AI delivers measurable societal value?

Dr. Kiran D. Sekhar of Kiran Fertility Clinics said reproductive medicine has shifted from standardized protocols to data-driven customization.

“Earlier, hormone doses were broadly standardized,” she said. “Now AI tailors them based on age, hormone levels, and ovarian reserve. That has significantly improved pregnancy rates.”

In IVF labs, oocyte maturity, which was once assessed subjectively, is now evaluated by AI systems with nearly 97% accuracy. AI also identifies the precise injection point for procedures such as ICSI, improving procedural consistency.

Embryo monitoring has evolved from periodic manual checks to continuous time-lapse imaging. AI-enabled scopes capture images every 10 minutes over five days, producing a full developmental record without disturbing embryos.

“Selecting the best embryo used to be subjective, almost like judging a beauty pageant,” Dr. Sekhar said. “Now AI gives us objective assessments with about 97% accuracy.”

Oncology From Detection to Decision

In cancer care, AI is influencing the full continuum: from prevention and diagnosis to treatment and monitoring.

“Cancer is time-dependent,” said Dr. Swarupa Mitra of Fortis Medical. “The quicker the diagnosis, the earlier we can begin treatment, often at Stage I or II, which significantly improves outcomes.”

AI tools are accelerating early detection, including in remote settings. Treatment pathways are increasingly individualized, with AI integrating genomics, imaging, pathology and electronic health records to guide therapy choices.

“Essentially, AI means making things easier, and in cancer care, that is critical.”

In radiation oncology, precision is critical. AI systems help target tumors while sparing healthy tissue, reducing surgical time and minimizing collateral damage. Hospitals are also using AI to predict toxicity risks and streamline logistics, from outpatient scheduling to bed management.

“AI has enhanced both clinical outcomes and operational efficiency,” Dr. Mitra said.

Cardiology From Reaction to Prevention

Dr. Tanuj Bhatia of SGRR Medical College said cardiology has relied on algorithmic support for decades through automated ECG interpretation.

“We’ve actually been using AI since the early 2000s,” he said, referring to automated ECG systems that helped detect early signs of heart attacks.

In acute myocardial infarction, where minutes determine survival, AI has reduced diagnostic delays. More significantly, predictive models now estimate high-risk cardiac events and mortality probability before they occur.

“Preventing a death event is one of the most remarkable innovations AI has brought to cardiology,” he said.

AI is also embedded in imaging systems such as optical coherence tomography to guide stent placement and vessel measurement. In AI-assisted vacuum systems like Penumbra devices, clinicians receive real-time audio-visual cues during procedures.

“Earlier, outcomes depended entirely on operator alertness. Now AI guides us,” Dr. Bhatia said.

Hospital Innovation and Public Health Impact

Beyond clinical settings, hospitals are redesigning workflows.

Dr. Bishnu Panigrahi of Fortis Healthcare described innovation cells aimed at simplifying the patient journey.

“From the moment a patient enters the hospital, they should feel they are in the right place with the right doctors,” he said.

Chatbots, QR-based navigation, automated documentation and AI-enabled insurance approvals are reducing friction. Administrators are also automating non-clinical tasks that burden nurses, freeing them for bedside care.

A recent visit to a smart hospital in Singapore reinforced another insight: nurses account for nearly 70% of healthcare delivery but are burdened with administrative tasks.

“Many non-nursing tasks were automated, freeing nurses to focus on bedside care,” he said. Similar systems are now being implemented in India.

AI-driven radiology tools are enabling earlier detection of conditions such as lung cancer, shifting care toward prevention rather than crisis management.

While clinicians spoke of outcomes and efficiency, policymakers addressed governance. Nico Schiettekatte from the Embassy of the Kingdom of the Netherlands traced the Netherlands’ AI journey.

In 2019, the country launched a national program called “Valuable AI in Healthcare,” stimulating AI pilots and issuing ethical guidelines. A year ago, the World Health Organization designated Delft’s Digital Ethics Center as the first WHO Collaborating Center on AI Health Governance.

Building on that, a 2025 policy note titled “Realization of AI in Healthcare” focused on moving from experimentation to implementation.

Central to Europe’s strategy is the EU AI Act, the world’s first comprehensive legal framework for AI systems. Based on a risk-classification model, it categorizes AI into unacceptable, high, limited, and minimal risk.

“It’s not just bureaucracy,” he said. “It creates a level playing field and ensures responsible implementation.”

Alongside regulation, the EU has committed €1 billion under its Apply AI Strategy to accelerate adoption across sectors, including healthcare, ensuring market access for AI-enabled medical devices without compromising patient safety.

Across both sessions, one message was clear: AI in healthcare is no longer an experiment. It is embedded in fertility labs, oncology wards, cardiac cath labs, and hospital administration systems.

But scaling AI responsibly requires more than algorithms. It demands regulatory clarity, ethical guardrails, workforce adaptation, and above all, trust, the speakers said.