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AI in Radiology: Shedding Light on Trust

July 14, 2026

Radiologists are increasingly relying on artificial intelligence to help with their workload, but there's a catch: they need to understand how these AI systems make decisions. That's where explainable AI comes in. A recent study looked at how different types of explanations affect radiologists' will

opinion

ChatGPT Falls Short in Bladder Cancer Diagnosis

July 14, 2026

Bladder cancer diagnosis is a complex process. Researchers looked at how well ChatGPT-4, a type of artificial intelligence, agrees with urologists on treatment plans. They used real patient data from 219 people who had a procedure called TURBT. The goal was to see if ChatGPT-4 could provide good adv

education

Chatbots in Dental Education: A New Frontier

July 13, 2026

The world of dentistry is evolving rapidly, and technology is playing a significant role in shaping its future. Recently, researchers compared the performance of three large language models - ChatGPT 5, Microsoft Copilot, and Google Gemini 3 - with dental students in restorative dentistry. They used

politics

Fresh Faces Fuel Climate Push

July 13, 2026

A new wave of progressive Democrats is set to shake up the House with a bold agenda that puts climate change and social justice at the forefront. These fresh faces, many of whom have unseated moderate incumbents, are determined to breathe new life into the Green New Deal. This ambitious plan, first

health

Telemedicine Acceptance in Turkey

July 13, 2026

In Turkey, a recent study explored how people's comfort with technology and their views on artificial intelligence affect their willingness to use telemedicine services. The study took place between January and March 2026 and involved 277 adults who visited a family health center. The participants

technology

Speeding Up Reinforcement Learning

July 13, 2026

Deep reinforcement learning is a powerful tool, but it's held back by its high computational demands. This makes it tough to use in real-world applications. One way to tackle this problem is by reducing the size of the neural networks used in reinforcement learning. However, most current methods for

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