According to a recent study, artificial intelligence can assist in identifying early indications of cancer in chest x-rays. Researchers discovered that a cutting-edge AI technology can distinguish between normal and pathological chest x-rays in a clinical context. Chest X-rays are used to diagnose a number of heart and lung diseases. A chest X-ray that is abnormal can be a sign of a number of illnesses, including cancer and long-term lung problems. According to scientists, a machine learning technology that can distinguish between normal and pathological chest X-rays will significantly lessen the radiologists' enormous burden.

The artificial intelligence algorithms behind the chatbot program ChatGPT -- which has drawn attention for its ability to generate humanlike written responses to some of the most creative queries -- might one day be able to help doctors detect Alzheimer's Disease in its early stages. Research from Drexel University's School of Biomedical Engineering, Science and Health Systems recently demonstrated that OpenAI's GPT-3 program can identify clues from spontaneous speech that are 80% accurate in predicting the early stages of dementia. Reported in the journal PLOS Digital Health, the Drexel study is the latest in a series of efforts to show the effectiveness of natural language processing programs for early prediction of Alzheimer's – leveraging current research suggesting that language impairment can be an early indicator of neurodegenerative disorders. The current practice for diagnosing Alzheimer's Disease typically involves a medical history review and lengthy set of physical and neurological evaluations and tests. While there is still no cure for the disease, spotting it early can give patients more options for therapeutics and support.

One of the NHS's leading hospital trusts has begun using artificial intelligence to help detect cancer in the gullet, which kills 8,000 Britons a year. It is hoped the technology will increase the number of cases of cancer in the oesophagus that doctors spot. Oesophageal cancer is one of the deadliest forms of cancer. It is hard to detect, particularly in its early stages, and many people who get it die soon after their diagnosis. Fewer than one in five of those diagnosed are still alive five years later.

But the earlier it's diagnosed, the more chances there are to delay its progression. Our joint team of researchers from IBM and University of Tsukuba has developed an AI model that could help detect the onset of the mild cognitive impairment (MCI), the transitional stage between normal aging and dementia -- by asking older people typical daily questions. In a new paper published in Frontiers in Digital Health journal, we present the first empirical evidence of tablet-based automatic assessments of patients using speech analysis -- successfully detecting mild cognitive impairment (MCI), the transitional stage between normal aging and dementia. Unlike previous studies, our AI-based model uses speech responses to daily life questions using a smartphone or a tablet app. Such questions could be as simple as inquiring someone about their mood, plans for the day, physical condition or yesterday's dinner. Earlier studies mostly focused on analyzing speech responses during cognitive tests, such as asking a patient to "count down from 925 by threes" or "describe this picture in as much detail as possible."