Infant nutrition and machine-based learning: Preliminary findings from Danone reveal colic promise By Cheryl Tay 06-Jul-2018 - Last updated on 06-Jul-2018 at 03:43 GMT Facebook Twitter Linkedin Email to a friend Machine-based learning could be as effective as the human ear when it comes to detecting infant crying or fussing, opening up possibilities for potential clinical applications such as detecting colic.Read the full story here. June's top 10 stories Nestlé signals personalised nutrition priority in Japan with launch of new DNA testing platform Probiotics and prebiotics in paediatric medicine: What are clinicians recommending? Infant nutrition and machine-based learning: Preliminary findings from Danone reveal colic promise Health claim changes aiding Japan industry but exports still a concern: Exclusive survey findings Probiotics and peanut allergy: Mounting evidence points to positive impact of supplementation Blackmores' brand accolade: Innovation and research 'key to maintaining consumer trust' Japanese firms target mass production of Spirulina to meet alternative protein demands Chr. Hansen sets sights on Indian expansion with patented probiotic strain WATCH: Astaxanthin — why consumers should love the 'Tinder of free radical scavengers' Ginseng extract a possible multi-target therapeutic tool against diabetes: Chinese review Prev 1 2 3 4 5 6 … 11 Next
