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INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS

《农业科学与工程前沿（英文）》 2023年第10卷第4期页码 648-653 doi: 10.15302/J-FASE-2023505

摘要：

Enhancement of farming management relies heavily on enhancing farmer knowledge. In the past, both the direct learning approach and the personnel extension system for improving fertilization practices of smallholders has proven insufficiently effective. Therefore, this article proposes an interactive knowledge learning approach using artificial intelligence as a promising alternative. The system consists of two parts. The first is a dialog interface that accepts information from farmers about their current farming practices. The second part is an intelligent decision system, which categorizes the information provided by farmers in two categories. The first consists of on-farm constraints, such as fertilizer resources, split application times and seasons. The second comprises knowledge-based practices by farmers, such as nutrient in- and output balance, ratios of different nutrients and the ratios of each split nutrient amount to the total nutrient input. The interactive knowledge learning approach aims to identify and rectify incorrect practices in the knowledge-based category while considering the farmer’s available finance, labor, and fertilizer resources. Investigations show that the interactive knowledge learning approach can make a strong contribution to prevention of the overuse of nitrogen and phosphorus fertilizers, and mitigating agricultural non-point source pollution.

关键词： artificial intelligence extension system non-point source pollution control smallholders fertilization

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Artificial intelligence in gastroenterology: where are we heading?

Joseph JY Sung, Nicholas CH Poon

《医学前沿（英文）》 2020年第14卷第4期页码 511-517 doi: 10.1007/s11684-020-0742-4

摘要： Artificial intelligence (AI) is coming to medicine in a big wave. From making diagnosis in various medical conditions, following the latest advancements in scientific literature, suggesting appropriate therapies, to predicting prognosis and outcome of diseases and conditions, AI is offering unprecedented possibilities to improve care for patients. Gastroenterology is a field that AI can make a significant impact. This is partly because the diagnosis of gastrointestinal conditions relies a lot on image-based investigations and procedures (endoscopy and radiology). AI-assisted image analysis can make accurate assessment and provide more information than conventional analysis. AI integration of genomic, epigenetic, and metagenomic data may offer new classifications of gastrointestinal cancers and suggest optimal personalized treatments. In managing relapsing and remitting diseases such as inflammatory bowel disease, irritable bowel syndrome, and peptic ulcer bleeding, convoluted neural network may formulate models to predict disease outcome, enhancing treatment efficacy. AI and surgical robots can also assist surgeons in conducting gastrointestinal operations. While the advancement and new opportunities are exciting, the responsibility and liability issues of AI-assisted diagnosis and management need much deliberations.

关键词： artificial intelligence endoscopy robotics gastrointestinal diseases

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The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social

Yujia Peng,Jiaheng Han,Zhenliang Zhang,Lifeng Fan,Tengyu Liu,Siyuan Qi,Xue Feng,Yuxi Ma,Yizhou Wang,Song-Chun Zhu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.006

摘要： The release of the generative pre-trained transformer (GPT) series has brought artificial general intelligence (AGI) to the forefront of the artificial intelligence (AI) field once again. However, the questions of how to define and evaluate AGI remain unclear. This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions (DEPSI). More specifically, we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system. The Tong test describes a value- and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI, allowing for infinite task generation. We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized, quantitative, and objective benchmarks and evaluation of AGI.

关键词： Artificial general intelligence Artificial intelligence benchmark Artificial intelligence evaluation Embodied artificial intelligence Value alignment Turing test Causality

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HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK

《农业科学与工程前沿（英文）》 2022年第9卷第1期页码 150-154 doi: 10.15302/J-FASE-2021419

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Artificial intelligence in radiotherapy: a technological review

Ke Sheng

《医学前沿（英文）》 2020年第14卷第4期页码 431-449 doi: 10.1007/s11684-020-0761-1

摘要： Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have occurred in the past 30 years. These advances, such as three-dimensional image guidance, intensity modulation, and robotics, created challenges and opportunities for the next breakthrough, in which artificial intelligence (AI) will possibly play important roles. AI will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others, particularly those with increased complexity because of technological advances. The improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the society. Furthermore, AI may provide new functionalities that facilitate satisfactory RT. The functionalities include superior images for real-time intervention and adaptive and personalized RT. AI may effectively synthesize and analyze big data for such purposes. This review describes the RT workflow and identifies areas, including imaging, treatment planning, quality assurance, and outcome prediction, that benefit from AI. This review primarily focuses on deep-learning techniques, although conventional machine-learning techniques are also mentioned.

关键词： artificial intelligence radiation therapy medical imaging treatment planning quality assurance outcome prediction

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Application of artificial intelligence in surgery

Xiao-Yun Zhou, Yao Guo, Mali Shen, Guang-Zhong Yang

《医学前沿（英文）》 2020年第14卷第4期页码 417-430 doi: 10.1007/s11684-020-0770-0

摘要： Artificial intelligence (AI) is gradually changing the practice of surgery with technological advancements in imaging, navigation, and robotic intervention. In this article, we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots. We conclude this review by summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery.

关键词： artificial intelligence surgical autonomy medical robotics deep learning

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人工智能走向2.0

潘云鹤

《工程（英文）》 2016年第2卷第4期页码 409-413 doi: 10.1016/J.ENG.2016.04.018

摘要：

随着互联网的普及、传感网的渗透、大数据的涌现、信息社区的崛起，以及数据和信息在人类社会、物理空间和信息空间之间的交叉融合与相互作用，当今人工智能(AI) 发展所处信息环境和数据基础已经发生了深刻变化，人工智能的目标和理念正面临重要调整，人工智能的科学基础和实现载体也面临新的突破，人工智能正进入一个新的阶段。这个源于传统而又与之不同的人工智能新阶段被称为人工智能2.0(AI 2.0)。本文从人工智能60 年的发展历史出发，通过分析促成人工智能2.0形成的外部环境与目标的转变，分析技术萌芽，提出了人工智能2.0 的核心理念，并结合中国发展的社会需求与信息环境特色，给出了发展人工智能2.0 的建议。

关键词：人工智能2.0 大数据群体智能跨媒体人机混合智能无人智能系统

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Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph

Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang

《医学前沿（英文）》 2020年第14卷第4期页码 488-497 doi: 10.1007/s11684-020-0762-0

摘要： Dyspnea is one of the most common manifestations of patients with pulmonary disease, myocardial dysfunction, and neuromuscular disorder, among other conditions. Identifying the causes of dyspnea in clinical practice, especially for the general practitioner, remains a challenge. This pilot study aimed to develop a computer-aided tool for improving the efficiency of differential diagnosis. The disease set with dyspnea as the chief complaint was established on the basis of clinical experience and epidemiological data. Differential diagnosis approaches were established and optimized by clinical experts. The artificial intelligence (AI) diagnosis model was constructed according to the dynamic uncertain causality graph knowledge-based editor. Twenty-eight diseases and syndromes were included in the disease set. The model contained 132 variables of symptoms, signs, and serological and imaging parameters. Medical records from the electronic hospital records of Suining Central Hospital were randomly selected. A total of 202 discharged patients with dyspnea as the chief complaint were included for verification, in which the diagnoses of 195 cases were coincident with the record certified as correct. The overall diagnostic accuracy rate of the model was 96.5%. In conclusion, the diagnostic accuracy of the AI model is promising and may compensate for the limitation of medical experience.

关键词： knowledge representation uncertain causality graphical model artificial intelligence diagnosis dyspnea

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人工智能与统计分析 Perspective

Bin YU, Karl KUMBIER

《信息与电子工程前沿（英文）》 2018年第19卷第1期页码 6-9 doi: 10.1631/FITEE.1700813

摘要：人工智能（artificial intelligence, AI）本质上是由数据驱动的。在其通过人机协作完成数据生成、算法开发与结果评估的任务中，需要应用许多统计概念。

关键词：人工智能；统计；人机协作

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Current applications of artificial intelligence for intraoperative decision support in surgery

Allison J. Navarrete-Welton, Daniel A. Hashimoto

《医学前沿（英文）》 2020年第14卷第4期页码 369-381 doi: 10.1007/s11684-020-0784-7

摘要： Research into medical artificial intelligence (AI) has made significant advances in recent years, including surgical applications. This scoping review investigated AI-based decision support systems targeted at the intraoperative phase of surgery and found a wide range of technological approaches applied across several surgical specialties. Within the twenty-one ( =21) included papers, three main categories of motivations were identified for developing such technologies: (1) augmenting the information available to surgeons, (2) accelerating intraoperative pathology, and (3) recommending surgical steps. While many of the proposals hold promise for improving patient outcomes, important methodological shortcomings were observed in most of the reviewed papers that made it difficult to assess the clinical significance of the reported performance statistics. Despite limitations, the current state of this field suggests that a number of opportunities exist for future researchers and clinicians to work on AI for surgical decision support with exciting implications for improving surgical care.

关键词： artificial intelligence decision support clinical decision support systems intraoperative deep learning computer vision machine learning surgery

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智能源于人、拓于工——人工智能发展的一点思考

蒋昌俊,王俊丽

《中国工程科学》 2018年第20卷第6期页码 93-100 doi: 10.15302/J-SSCAE-2018.06.015

摘要：

人工智能（AI）旨在模拟人脑中信息存储和处理机制等智能行为，使机器具有一定程度的智能水平。随着互联网、大数据、云计算和深度学习等新一代信息技术的飞速发展，目前AI领域的研究和应用已经取得重要进展。本文将深入分析与AI密切相关的计算机科学、控制科学、类脑智能、人脑智能等学科或领域之间的交融与历史演进；指出神经科学、脑科学与认知科学中有关脑的结构与功能机制的研究成果，为构建智能计算模型提供了重要的启发，并从逻辑模型及系统、神经元及网络模型、视觉神经分层机制等方面，分别阐述智能的驱动与发展；最后从互联网的计算理论、AI的演算和计算的融合、类脑智能的模型和机理、AI对神经科学的推动作用、反馈计算的算法设计与控制系统的能级五个方面，对AI的发展趋势进行了展望。

关键词：人工智能人脑智能类脑智能智能发展学科演进

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Special issue: Innovative applications of big data and artificial intelligence

《工程管理前沿（英文）》 2022年第9卷第4期页码 517-519 doi: 10.1007/s42524-022-0234-0

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统一集论与人工智能

张江,林华,贺仲雄

《中国工程科学》 2002年第4卷第3期页码 40-47

摘要：

通过综合经典集合、模糊集合、可拓集合、Vague集合、粗糙集合、集对分析、FHW（模糊灰色物元空间）、FEEC（模糊可拓经济控制）等多种理论，提出了统一集概念，并详细讨论统一集的各种运算以及相关性质。从分析集合理论和人类思维形式之间的关系人手，把统一集理论初步应用到模式识别、聚类分析、逻辑推理、机器学习、智能决策等多种人工智能领域，指出了集合论及其运算系统与逻辑推理系统的等价关系。统一集能对现有的理论进行总结、统一，还为开辟崭新的集合论、逻辑推理方法提供很好的理论基础。

关键词：统一集人工智能集合运算逻辑推理

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Comparative study of various artificial intelligence approaches applied to direct torque control of induction

Moulay Rachid DOUIRI, Mohamed CHERKAOUI

《能源前沿（英文）》 2013年第7卷第4期页码 456-467 doi: 10.1007/s11708-013-0264-8

摘要： In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS). The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque control (ANFIS-DTC). Compared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC), and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the electromagnetic torque and stator flux ripples, and incurs much shorter execution times and hence the errors caused by control time delays are minimized. The validity of the proposed methods is confirmed by simulation results.

关键词： adaptive neuro-fuzzy inference system (ANFIS) artificial neural network direct torque control (DTC) fuzzy logic induction motor

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基于人工智能的内容安全发展战略研究

朱世强,王永恒

《中国工程科学》 2021年第23卷第3期页码 67-74 doi: 10.15302/J-SSCAE-2021.03.004

摘要：

内容安全是指对信息内容的保护，以及信息内容符合政治、法律、道德层次的要求。人工智能的发展对内容安全产生了非常重要的影响。本文从基于人工智能的内容安全重大战略需求出发，梳理了国内外的研究现状与发展趋势，凝练了基于人工智能的内容安全的关键技术问题。研究提出，按照三步走的策略构建世界领先的基于人工智能的内容安全体系；在对抗性机器学习、可解释人工智能、混合增强智能、知识驱动的内容安全等方面开展技术创新突破，同时应注重政策法规和监管机制建设；建设面向内容攻防的网络靶场、面向舆情攻防的大规模社会系统模拟装置等内容安全重大基础设施。

关键词：人工智能，内容安全，体系建设

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标题作者时间类型操作

INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS

期刊论文

Artificial intelligence in gastroenterology: where are we heading?

Joseph JY Sung, Nicholas CH Poon

期刊论文

The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social

Yujia Peng,Jiaheng Han,Zhenliang Zhang,Lifeng Fan,Tengyu Liu,Siyuan Qi,Xue Feng,Yuxi Ma,Yizhou Wang,Song-Chun Zhu,

期刊论文

HIGH-PERFORMANCE COMPUTATION AND ARTIFICIAL INTELLIGENCE IN PESTICIDE DISCOVERY: STATUS AND OUTLOOK