Opinion It started in Jeopardy and ended in loss. IBM's flagship AI Watson Health has been sold to venture capitalists for an undisclosed sum thought to be around a billion dollars, or a quarter of what the division cost IBM in acquisitions alone since it was spun off in 2015. Not the first nor the last massively expensive tech biz cock-up, but isn't AI supposed to be the future? Isn't IBM supposed to be good at this? It all started so well.

Like many countries, China has a health care problem. Changing demographics and lifestyles mean demand for health care is outstripping growth in medical resources and its cost is rising faster than the insurance premium. With 250 million people over the age of 60, the world's most populous country is ageing. Diseases associated with more affluent societies, such as cardiovascular conditions and diabetes, are on the rise. China has 400 million chronic disease patients whose treatment costs 70% of total health care resources.

I was recently invited to judge a Data Science competition. The students were given the'heart disease prediction' dataset, perhaps an improvised version of the one available on Kaggle. I had seen this dataset before and often come across various self-proclaimed data science gurus teaching naïve people how to predict heart disease through machine learning. I believe the "Predicting Heart Disease using Machine Learning" is a classic example of how not to apply machine learning to a problem, especially where a lot of domain experience is required. Let me unpack the various problems in applying machine learning to this data set.

I was recently invited to judge a Data Science competition. The students were given the'heart disease prediction' dataset, perhaps an improvised version of the one available on Kaggle. I had seen this dataset before and often come across various self-proclaimed data science gurus teaching naïve people how to predict heart disease through machine learning. I believe the "Predicting Heart Disease using Machine Learning" is a classic example of how not to apply machine learning to a problem, especially where a lot of domain experience is required. Let me unpack the various problems in applying machine learning to this data set.

SoftBank Group has made several big name investments across insurtech and real estate, including deals to WeWork, OYO Rooms, PolicyBazaar, and Lemonade. SoftBank wants its portfolio companies to get along. Since 2014, SoftBank has been investing aggressively in companies modernizing insurance and real estate. Armed with its massive $98B Vision Fund, it hasn't been shy to write huge checks to startups disrupting these areas. The average size of Vision Fund-backed equity deals to insurtech and real estate startups exceeds $400M, and the Vision Fund has accounted for 8% of all deals by SoftBank Group in these areas since 2014.

Japanese billionaire Masayoshi Son, the founder and chief executive of technology conglomerate SoftBank Group Corp, is known for making solid bets in China's hi-tech sector. Around 18 years ago, Son's company invested US$20 million in a small Chinese online retail platform that rapidly grew to become e-commerce giant Alibaba Group Holding. Son in July invited the heads of fast-rising Chinese companies Ping An Good Doctor and Didi Chuxing to a party he hosted in Tokyo, in a testament to how far these two firms have grown since SoftBank invested in them. Wang Tao, the founder, chairman and chief executive of Ping An Good Doctor, acknowledged Son's contribution amid the Hong Kong-listed online health care provider's efforts to innovate and extend its operations outside the mainland. "Mr Son helped us a lot in our international expansion," said Wang in an interview with the South China Morning Post on the sidelines of the fifth World Internet Conference held earlier this month in Wuzhen, a town in China's eastern coastal province of Zhejiang.

LONDON (Reuters) - Softbank's Vision Fund plans to pump more money into insurance, a sector it sees as both ripe for disruption and a potential booster for its bigger bets in cars, health and financial services, a Vision Fund executive told Reuters. In the past year, the world's biggest private technology investor has backed China's largest online insurer ZhongAn (6060.HK) as well as PolicyBazaar, India's biggest online insurance distributor, and app-based U.S. home insurer Lemonade. And these and other insurance bets totaling nearly $3 billion are just the start, Vision Fund dealmaker David Thevenon said. The Vision Fund has raised nearly $100 billion, almost half of it from Saudi Arabia's sovereign wealth fund. "We believe that technology and how data is used, processed and collected is going to transform insurance," Thevenon said.

Qu Jianguo, 64, had a futuristic medical visit in Shanghai as he put his wrist through an automated pulse-taking machine and received the result within two minutes on a mobile phone – without a doctor present. The small device, which has a half-open clasp that records the heartbeat, is one of the technologies developed by hi-tech firms aiming to help China offset its shortage of physicians by combining big data and artificial intelligence (AI). The machine made by Ping An Good Doctor was shown off at the 2018 World AI Expo in Shanghai at a time when Chinese policymakers are making a major push to turn the country into a global tech leader. "I came here to see how Chinese-style medical treatment could be done without a doctor. That would be really convenient," said Qu, a retired IT worker attending the expo.

Remote medical consultation services that connect doctors and patients via smartphones and other devices are spreading across Japan, with their popularity boosted by recent deregulation of telemedicine. Under deregulation in April, health insurance can now be used for such consultations, and health care startups are expected to further accelerate the development of remote health care services that use artificial intelligence amid wider accumulation of health data on individuals. The Health, Labor and Welfare Ministry unveiled its vision for developing and utilizing a health care database to support telemedicine applications for remote diagnosis, remote treatment and telesurgery in its proposal titled "The Japan Vision: Health Care 2035," along with changes in the social environment, including a rapidly aging population and the advancement of medical technology. As an experiment for remote consultations, this reporter tried using the health care mobile app called curon, which is operated by Tokyo-based health care startup Micin Inc. After explaining via smartphone that "I have been taking large amounts of painkillers because I have been bothered by frequent headaches and fevers recently," a doctor., who appeared in a videophone call replied, "You'll lessen the strain on your stomach and kidneys if you change your medication."

In this picture taken on December 13, 2017, patients wait in a hospital in Baoding. With their mobile payment and online shopping services, China's big internet companies have transformed consumption habits in the country. Now they're extending their reach into China's healthcare sector, which has long been searching for ways to help overburdened doctors. Unlike in the U.S., where tech giants such as Apple or Amazon have only just made their healthcare ambitions known by building clinics for employees, China's tech companies have been experimenting with online healthcare for the past few years. From smaller startups to behemoths like Alibaba and Tencent, firms are trying to improve hospital efficiency by creating online appointment and diagnostic apps.