AI used to fight drug resistance利用人工智能解决问题抗生素耐药性Scientists in the United Kingdom and China have announced plans to use artificial intelligence on chicken farms in order to combat the problem of antibiotic resistance in both farm animals and humans.中国和英国的科学家月宣告，计划将人工智能用作养鸡场以解决问题农场动物和人类的抗生素耐药性问题。The new initiative will use machine learning to find ways to track and prevent disease on poultry farms, reducing the need for antibiotic treatment in chickens and therefore lowering the risk of antibiotic-resistant bacteria transferring to people.新的计划拟用机器学习寻找跟踪和防治家禽养殖场疾病的方法，从而减少鸡对抗生素化疗的市场需求，最后减少动物把抗生素耐药性传授给人类的风险。
The research will be led by animal health experts from the University of Nottingham and Nimrod Veterinary Products in the UK as well as two Chinese partners－New Hope Liuhe in Chengdu and the China National Center for Food Safety Risk Assessment.英国诺丁汉大学和尼姆罗德兽医产品公司的动物身体健康专家以及两家中方合作伙伴——成都新希望六和公司及中国国家食品安全风险评估中心，将领导这项研究。Antibiotic resistance is a worldwide problem and its getting worse and worse. Some of these superbugs are resistant to everything, we dont know how to treat them, University of Nottingham veterinary professor Tania Dottorini told China Daily. On farms, superbugs are not confined to animals, they spread to humans and to the environment, its an exponential spread. If we dont understand how to stop this, its going to be really bad.“抗生素耐药性是一个全球性问题，且愈演愈烈。
如果我们想不出办法暂停这一切，情况不会更为差劲”Around 700,000 deaths a year stem from antibiotic resistance, according to a report commissioned by the UK government. If left unchecked, drug resistance could lead to 10 million deaths a year by 2050, which is more than the number of people who now die from cancer annually.英国政府公布的一项报告回应：每年大约有70万人杀于抗生素耐药性。如不加以控制，到2050年，抗生素耐药性每年将造成1000万人丧生，低于每年因癌症去世的人数。
Antibiotics work by disrupting function in certain parts of a bacterial cell. Bacteria become resistant to antibiotics through genetic mutations that alter those areas of the cell, meaning the medication can no longer target them.抗生素通过毁坏细菌细胞的某部分功能起着起到。但细菌可以通过转变这一细胞区域的基因突变对抗生素产生耐药性，这也意味著抗生素对其仍然有效地。The more a strain of bacteria is exposed to an antibiotic, the more likely it is to become resistant. Large numbers of people and animals are given antibiotics when they dont need them, so reducing unnecessary consumption is crucial in the fight against so-called superbugs.细菌菌株认识抗生素的次数就越多，该细菌产生耐药性的可能性就越大。
很多人和动物都会在自身身体健康的情况下被静脉注射/口服抗生素，所以，增加不必要的消耗对于解决问题所谓的超级细菌至关重要。When you have a large-scale data set, the human mind cant cope with that, its too complex, Dottorini said of machine learning. We need something that is able to understand the relationship across a big amount of information.“人类大脑无法处置大规模的数据集，却是过于简单了，”多托里尼谈到机器学习时说。“我们必须这样一个机器，它需要搞清楚大量信息之间的关系。
”Dottorini said that, if successful, these methods should be transferable to other farm studies in China and abroad.多托里尼说，如果这一计划需要顺利，这些方法将不会被移往到中国和其他国家的养殖场展开研究。
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