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Mechanical Fetal Simulator for Fetal Doppler Testing 机械胎儿模拟器胎儿多普勒检测
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.5
Arum Triwerdani, Syaifudin Syaifudin, B. Utomo, Abdul Basit
The continuous use of fetal Doppler allows for discrepancies in values ​​that lead to misdiagnoses in patients. This study aims to determine the effect of sound source distance on the fetal simulator with the measurement point. The contribution of this research is that the mechanical fetal heart system has 4 distances so that later it can be analyzed whether there is an influence of the location of the sound source on the accuracy of measurements using a fetal simulator. To get the desired distance, a solenoid is used which ends with a pipe of 2 cm, 5 cm, 10 cm, and 50 cm respectively. The solenoid used in the fetal simulator functions as a producer of the fetal heart. There is a rotary switch that functions for solenoid selection, namely 2 cm, 5 cm, 10 cm and 50 cm solenoids. Data collection was carried out on each solenoid and by placing the Doppler probe perpendicular and tilted. On the solenoid with a distance of 50 cm all measurement results exceed the allowable tolerance limit. The results showed that the BPM value of the two Doppler brands did not have a significant difference in value. When measuring fetal Doppler, the largest error value was 2.67%. The results of this study can be used as a reference when conducting an examination
持续使用胎儿多普勒允许差异的值,导致误诊的病人。本研究旨在通过测点确定声源距离对胎儿模拟器的影响。本研究的贡献在于机械胎心系统有4个距离,以便以后可以分析声源的位置是否对胎儿模拟器测量精度有影响。为了获得所需的距离,使用螺线管,其两端分别为2厘米,5厘米,10厘米和50厘米的管道。在胎儿模拟器中使用的螺线管作为胎儿心脏的生产者。有一个旋转开关,可以选择螺线管,即2厘米,5厘米,10厘米和50厘米的螺线管。通过垂直和倾斜放置多普勒探头,对每个螺线管进行数据收集。在距离为50cm的电磁阀上,所有测量结果均超过允许公差限制。结果显示,两种多普勒品牌的BPM值在数值上没有显著差异。在测量胎儿多普勒时,最大误差值为2.67%。本研究结果可作为检查时的参考
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引用次数: 1
Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor 光子晶体传感技术在肿瘤检测中的应用
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.2
Sunil Sharma, L. Tharani
Tumors can cause severe problem to human beings. Sometime it can be a cause of death. Earlier there were lack of treatment and technological deficiency, due to which it was unable to detect tumor cells and even unable to offer proper treatment for these diseases.   This study aims to use Photonic crystal (PhC) due to their ample choice of structures and litheness to endure with every sphere of influence has been utilized them twenty decade back to now a day and have extremely huge prospects in imminent future also. They have revealed their incidence in the field of imaging, sensing, fabricating industries, automation, medical, mechatronics, computronics, mechanochromic, underwater acoustic detection, pharma industries and nanoimprinting etc. If we are discussing about current and impending applications of PhC then it comprises smart sensing and detection of disunite diseases, anonymous viruses and a range of tumors. Artificial intelligence (AI) is also playing incredibly essential role in analyzing and creating entities equivalent to the change in human behavior. AI tools and techniques are utilizing to create intelligent entities through which it is accomplishing countless feats. The PhC along with the artificial intelligence are utilizing as Optical Neural Network (ONN), Artificial Neural Network (ANN), Cellular Computing, Plasma Technology, Parallel Processing, Image Processing etc. Here in this study designated photonic crystal has been used for the detection of infected cell in human body. Sometimes these infected cells are unable to trace by normal pathological investigations and slowly they take a shape of Tumors. But thanks to Photonics crystal sensors that they have made it true not only for detection but we can say for early detection of such tumors in human body. These early detection and proper investigation is possible only because of AI impacts on photonics crystal. This study focuses on detection and observation of bio molecules for selectivity, sensitivity, reflectivity and concentration. By change in wavelength i.e. from 1.5 μm to 4 μm the refractive index (RI) of tumor cell can be measured which is observed by measuring sensitivity between 11258 nm/RIU to 32358 nm/RIU. Tumors have refractive indices varies between 1.3342 to 1.4251. It is observed that sarcoma level is directly proportional to the RI of tumor. Various AI algorithms like support vector machine (SVM) obtained accuracy as 96%, K- nearest neighbor (KNN) shows as 70%, logistic regression (LR) shows as 88%, random forest (RF) show it as 90%, fuzzy logic (FL) and artificial neural network (ANN) observed accuracy as 93% and 95% respectively.
肿瘤会给人类带来严重的问题。有时它会导致死亡。早些时候,由于缺乏治疗和技术缺陷,无法检测肿瘤细胞,甚至无法为这些疾病提供适当的治疗。本研究的目的是利用光子晶体(PhC),由于其丰富的结构选择和轻便性,以适应各个领域的影响,二十多年来一直在使用,在不久的将来也有非常巨大的前景。它们在成像、传感、制造工业、自动化、医疗、机电一体化、电子、机械变色、水声探测、制药工业和纳米印迹等领域都有广泛的应用。如果我们讨论的是PhC当前和即将到来的应用,那么它包括对不统一疾病、匿名病毒和一系列肿瘤的智能传感和检测。人工智能(AI)在分析和创造相当于人类行为变化的实体方面也发挥着不可思议的重要作用。人工智能工具和技术被用来创造智能实体,通过它可以完成无数的壮举。PhC与人工智能一起应用于光神经网络(ONN)、人工神经网络(ANN)、细胞计算、等离子体技术、并行处理、图像处理等。本研究将指定光子晶体用于人体感染细胞的检测。有时这些被感染的细胞无法被正常的病理检查所追踪,慢慢地形成肿瘤的形状。但是多亏了光子晶体传感器,他们不仅实现了检测,而且我们可以说是实现了对人体肿瘤的早期检测。这些早期发现和适当的调查是可能的,因为人工智能对光子晶体的影响。本研究的重点是对生物分子的选择性、灵敏度、反射率和浓度的检测和观察。通过波长的变化,即1.5 μm到4 μm,可以测量肿瘤细胞的折射率(RI),测量灵敏度在11258 nm/RIU到32358 nm/RIU之间。肿瘤的折射率在1.3342到1.4251之间。观察到肉瘤的水平与肿瘤的RI成正比。支持向量机(SVM)的准确率为96%,K近邻(KNN)的准确率为70%,逻辑回归(LR)的准确率为88%,随机森林(RF)的准确率为90%,模糊逻辑(FL)和人工神经网络(ANN)的准确率分别为93%和95%。
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引用次数: 2
Comparison of Air Pressure Control Between Discrete and PID Control Applied in the Calibration Process in Blood Pressure Meter 离散控制与PID控制在血压计标定过程中的比较
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.6
Harisha Avin Nurcahyana, T. Indrato, Triana Rahmawati, W. Caesarendra
In performing the calibration of the sphygmomanometer, the officer needs to first reset the installation and pump the bulb slowly until it reaches the set point in accordance with the calibration settings where this does not provide convenience to the calibration officer. So the author wants to do research on making additional devices to support DPM calibration instruments that have been commercialized to speed up the pump process in Sphygmomanometer calibration. The purpose of this research is to make an Automatic Pump module with PID control to analyze the stability of the pressure achievement in accordance with the set point when using the smoothing program or not. This study used set points of 50, 100, 150, 200, and 250 mmHg. Data retrieval was carried out within 260 seconds at each set point at the Campus of the Department of Electrical Engineering Poltekkes Kemenkes Surabaya. The results of this study indicate that the tool testing using the smoothing program experienced small oscillations compared to the program without smoothing. The data obtained are at setting 50 the average overshoot is 54 and the average undershoot is 49; at setting 100 the average overshoot is 109 and the average undershoot is 99; at setting 150 the average overshoot is 156 and the average undershoot is 149; at setting 200 the average overshoot is 206 and the average undershoot is 196; at setting 250 the average overshoot is 253 and the average undershoot is 247. The importance of this device was made in order to make it easier and faster for the calibration officer to calibrate the Sphygmomanometer.
在执行血压计的校准时,工作人员需要首先重置安装并缓慢泵送灯泡,直到根据校准设置达到设定点,这对校准人员来说不方便。因此,笔者希望研究制造额外的设备来支持已经商业化的DPM校准仪器,以加快血压计校准的泵浦过程。本研究的目的是制作一个带有PID控制的自动泵模块,分析在使用或不使用平滑程序时,压力值是否按照设定值稳定。本研究采用了50、100、150、200和250 mmHg的设定值。在电气工程系Poltekkes Kemenkes Surabaya校园的每个设定点,数据检索在260秒内进行。研究结果表明,与不使用平滑程序相比,使用平滑程序的刀具测试经历了较小的振荡。在设定50时获得的数据,平均超调54,平均欠调49;设置为100时,平均超调值为109,平均过调值为99;设置为150时,平均超调值为156,平均过调值为149;设置200时,平均超调值为206,平均过调值为196;在设置250时,平均超调是253,平均过调是247。这个装置的重要性是为了使校准人员更容易和更快地校准血压计。
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引用次数: 0
Measurement of Vital Signs Respiratory Rate Based on Non Contact Techniques Using Thermal Camera & Web Camera with Facial Recognition 基于非接触式热像仪和带有面部识别的网络摄像机的生命体征呼吸频率测量
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.3
Raden Duta Ikrar Abadi, Endro Yulianto, Triwiyanto Triwiyanto, Sandeep Kumar Gupta, Vugar Abdullayev
Examination of the respiratory rate is included in the calculation of vital sign parameters used by the medical team to determine whether a person's condition is good or not. Researchers want to develop a method of checking the respiratory rate that is easy to use by the general public and can display fast and precise results. During this pandemic, we are forced to reduce direct human-to-human contact with the aim of suppressing the exchange of viruses. From this condition, the researcher wants to develop a measuring instrument to measure the respiratory frequency with the non-contact method. This method is expected to reduce direct contact between humans and still get the results of the respiratory rate value which can be used as a parameter to determine a person's condition. To get the value of the respiratory rate, researchers have an idea by monitoring changes in temperature using a thermal camera. For the respiratory rate parameter, the researcher observed the nose area by detecting changes in expiratory and inspiration temperatures and then calculating the respiratory rate. To get these results, the researcher uses a method of detecting the face area or called face recognition and then detecting the ROI point in the area of interest in the nose area. In observing the respiratory rate, the temperature value during expiration is 31.05 °C while at the time of inspiration is 30.01 °C. This temperature difference will be carried out in the process of calculating the respiration rate value by the system made by the researcher. In the results of this study, it was found that the respiration rate module can be used as a reference with a normal use range of 60-120 cm with an error value of 1% if the distance is above 100 cm, then the results of this study are that this research can be implemented on a breathing frequency measuring instrument with a non-standard method. - contact
医疗团队在计算生命体征参数时,也会检查呼吸频率,以确定一个人的状况是否良好。研究人员希望开发出一种便于大众使用、能够快速准确显示结果的呼吸频率检测方法。在这次大流行期间,我们被迫减少人与人之间的直接接触,目的是抑制病毒的交流。针对这种情况,研究人员希望研制一种非接触式呼吸频率测量仪器。这种方法有望减少人与人之间的直接接触,并且仍然可以得到呼吸频率值的结果,该值可以用作确定一个人的病情的参数。为了得到呼吸频率的值,研究人员有一个想法,通过使用热像仪监测温度的变化。对于呼吸速率参数,研究人员通过检测呼气和吸气温度的变化来观察鼻子区域,然后计算呼吸速率。为了得到这些结果,研究人员使用了一种检测面部区域或称为面部识别的方法,然后在鼻子区域的感兴趣区域检测ROI点。观察呼吸速率,呼气时温度值为31.05℃,吸气时温度值为30.01℃。这个温差将在研究者制作的系统计算呼吸速率值的过程中进行。在本研究的结果中发现,如果距离在100 cm以上,呼吸速率模块可以作为参考,正常使用范围为60-120 cm,误差值为1%,那么本研究的结果是,本研究可以在呼吸频率测量仪上以非标准方法实现。——联系
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引用次数: 0
Use of a Portable Particle Counter to Analyze Particle Stability Time in a Biological Safety Cabinet (BSC) 使用便携式粒子计数器分析生物安全柜(BSC)中粒子稳定时间
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.4
Herlina Candra Putri, Priyambada Cahya Nugraha, Endro Yulianto, A. Bhatt
Biological Safety Cabinet (BSC) is a laboratory work area with air ventilation that has been engineered to protect workers working with material samples, the environment and material samples from the possible danger of contamination or causing the spread of pathogenic bacteria or viruses. The purpose of this study is to analyze the stability of the time required for the BSC to reach the condition of no particles in the BSC space. This is done by making a module using the PMS7003 sensor to detect the number of particles. This study uses the Arduino Mega system for data processing and then displays it in the form of graphs and numbers. In the condition of the number of particles of 162,965, the time required for the BSC is 29 seconds, while in the condition of the number of particles of 186,408, the time required is 38 seconds. So it is known that if the number of particles in the BSC space is more and more particles in the BSC space, the longer it takes for the BSC to reach the no-particle condition. BSC that uses a single fan blower cannot achieve a stable number of particles simultaneously.
生物安全柜(BSC)是一个具有空气通风的实验室工作区域,其设计目的是保护工作人员与材料样品,环境和材料样品一起工作,免受可能的污染或引起致病菌或病毒传播的危险。本研究的目的是分析平衡计分卡达到平衡计分卡空间无粒子状态所需时间的稳定性。这是通过使用PMS7003传感器制作一个模块来检测粒子的数量来完成的。本研究使用Arduino Mega系统对数据进行处理,然后以图形和数字的形式显示。在粒子数为162,965的情况下,BSC所需时间为29秒,而在粒子数为186,408的情况下,所需时间为38秒。由此可知,如果BSC空间中的粒子数越来越多,则BSC达到无粒子状态所需的时间越长。使用单个风机的平衡记分卡无法同时达到稳定的颗粒数量。
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引用次数: 0
Analysis of X-Ray Beams Irradiation Accuracy Using Collimation Test Tools as Well as Illumination Measurement on the Collimator to the Radiographic X-Ray Machine Conformity Test Results 准直检测工具对x射线光束辐照精度的分析及准直仪照度测量对x射线机一致性检测结果的影响
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.8
M Roziq, T. Indrato, M. Ridha Mak’ruf
In the Suitability Test Method there is the Illumination and Collimation Test still using the manual method. This test aims to ensure that the light from the collimator lamp can be seen clearly so that the area of ​​the irradiation field can be identified when irradiating, as well as ensuring that the area of ​​the collimator lamp matches the X-ray beam so that it meets the needs and ensures that the patient does not get an excessive dose. The purpose of this research is to develop the simplest way by which the illumination measurement is carried out simultaneously at four points and the measurement data is directly stored. The contribution of this research is expected to be more testing tools and the data will be stored until the effective time of the next test. This module is designed using the HC-SR04 sensor as a distance meter and the TSL2561 sensor as a lux meter. The TSL2561 sensor allows for precise Lux calculations and can be configured for different gain/timing ranges to detect light ranging from 0.1-40,000+ Lux on the fly. This module is equipped with a display facility in the form of TFT Nextion to display measurement results. In addition, there is also data storage using an SD Card to store display measurement results. In this research, the module has been tested and compared with the suitability test value of the X-ray plane and got an error value of 2.0% with a module efficiency of 98.0% in the illumination test, and an error of 2.2% with a module efficiency of 97.8% in the collimator test. From this research, it can be concluded that the light sensor TSL2561 can be used to measure the illumination area of ​​the collimator lamp.
在适用性测试方法中,照明和准直测试仍然使用手动方法。该测试的目的是确保准直灯发出的光清晰可见,以便在照射时确定照射场的面积,并确保准直灯的面积与x射线光束匹配,使其满足需要,并确保患者不会获得过量剂量。本研究的目的是开发一种最简单的方法,通过该方法可以同时在四个点进行照明测量,并直接存储测量数据。期望本研究的贡献是提供更多的测试工具,并将数据保存到下次测试的有效时间。本模块采用HC-SR04传感器作为测距仪,TSL2561传感器作为勒克斯计。TSL2561传感器允许精确的勒克斯计算,并可以配置为不同的增益/定时范围,以检测0.1-40,000+勒克斯的光。该模块配有TFT Nextion形式的显示设备,用于显示测量结果。此外,还有数据存储,使用SD卡存储显示测量结果。在本研究中,对该模块进行了测试,并与x射线平面的适用性测试值进行了比较,光照测试的误差值为2.0%,模块效率为98.0%;准直仪测试的误差值为2.2%,模块效率为97.8%。通过本研究,可以得出光传感器TSL2561可以用来测量准直灯的照明面积。
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引用次数: 0
Effect of Irradiation Distance on Tube Voltage Measurement and X-Ray Device Time Using Scintillator 辐照距离对闪烁体测量管电压和x射线器件时间的影响
Pub Date : 2022-04-29 DOI: 10.35882/jeeemi.v4i2.7
All Adin Nurhuda, M. R. Mak'ruf, T. Indrato, Sari Luthfiyah
The results of the output of the X-ray device are very important to know how much the correct value, whether it is in accordance with the arrangements made by radiology personnel or there is a difference even deviation of the value out of the arrangement. This conformity test activity needs a testing tool that is often used by BAPETEN personnel to find out how much the output value of KV, Time, Dose, Room leak, mA and mAs from an X-ray device unit. The purpose of this study was to analyze the effect of irradiation distance on tube voltage measurements and X-ray device time using Scintillators. The study used scintillator sensors to detect radiation, arduino as a programming source, bluetooth HC-05 as digital communication between hardware and PC, PC / Delphi as display. This research design is Pre-Experimental with After Only Design research type. Where the author takes data compared to standard tools then analyzes the data. The results showed the largest error at a distance of 120cm with a 90 KV setting of 43.52%. And the smallest error is at a distance of 120cm with a 50 KV setting of 0.07%.
x射线装置输出的结果是非常重要的,要知道多少数值是正确的,是按照放射学人员所作的安排还是有差异甚至偏离了安排的数值。该符合性测试活动需要BAPETEN人员经常使用的测试工具,以确定x射线设备单元的KV,时间,剂量,房间泄漏,mA和mA的输出值。本研究的目的是分析辐照距离对闪烁体测量管电压和x射线装置时间的影响。本研究采用闪烁体传感器检测辐射,arduino作为编程源,蓝牙HC-05作为硬件与PC之间的数字通信,PC / Delphi作为显示。本研究设计为预实验与事后设计研究类型。作者将数据与标准工具进行比较,然后分析数据。结果表明,在90 KV设置下,在120cm距离处误差最大,为43.52%。在50kv设置0.07%的情况下,在120cm距离处误差最小。
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引用次数: 0
Heating and Cooling Rate Study on Water Cooling Thermal Cycler using Aluminium Block Sample 铝块水冷式热循环器的加热和冷却速率研究
Pub Date : 2022-03-04 DOI: 10.35882/jeeemi.v4i2.1
N. B. Wicaksono, Sukma Meganova Effendi
Temperature measurement has many applications in medical devices. In recent days, body temperature become the main screening procedure to justify people infected by SARS-CoV-2. Related to pandemic situation due to SARS-Cov-2, Polymerase Chain Reaction (PCR) method become the most accurate and reliable detection method. This method employs a device named PCR machine or Thermal Cycler. In this research, we focus to build a Thermal Cycler using a low-cost material such as aluminium and using a liquid coolant as the cooling system. We use 2 types of coolant solution: mineral water and generic liquid coolant. Peltier device in thermal cycler serves as heating and cooling element. In heating rate experiments, generic liquid coolant shows a better result than using mineral water due to specific heat capacity and thermal conductivity of water. In the cooling rate experiments, the water pump is activated to stream the liquid solution, the flow rate of liquid solution is influenced by viscosity of the liquid. Generic liquid coolant has approx. 4,5 times greater viscosity than water. The higher flow rate means better performance for cooling rate. Using 2 pieces of 60-Watt heaters and a 60-Watt chiller and aluminium material as block sample, our research shows a heating and cooling rate up to approx. 0,1°C/s. Compared to commercially thermal cycler, our thermal cycler has a lower wattage; this lower wattage performance has been tradeoff with lower ramping rate. Some factors are suspected become the source of contributors of lower ramping rate.
温度测量在医疗设备中有许多应用。最近几天,体温成为判断是否感染SARS-CoV-2的主要筛查程序。与SARS-Cov-2大流行形势相关,聚合酶链反应(PCR)方法成为最准确、最可靠的检测方法。该方法采用PCR机或热循环仪。在这项研究中,我们的重点是建立一个热循环使用低成本的材料,如铝和使用液体冷却剂作为冷却系统。我们使用2种冷却剂溶液:矿泉水和通用液体冷却剂。热循环器中的珀耳帖装置作为加热和冷却元件。在加热速率实验中,由于水的比热容和导热系数,普通液体冷却剂比矿泉水表现出更好的效果。在冷却速率实验中,启动水泵使液液流动,液液的流速受液体粘度的影响。一般的液体冷却剂有大约。粘度是水的4、5倍。流速越高,冷却速率越好。使用2个60瓦的加热器和一个60瓦的冷水机和铝材料作为块样品,我们的研究表明,加热和冷却的速度高达约。0 1°C / s。与商用热循环器相比,我们的热循环器具有更低的瓦数;这种较低的瓦数性能与较低的爬坡率相权衡。一些因素被怀疑是降低斜坡率的来源。
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引用次数: 0
Analysis Of Baby Incubator Humidity Based PID with Kangaroo Mode 基于袋鼠模式的婴儿培养箱湿度PID分析
Pub Date : 2022-01-20 DOI: 10.35882/jeeemi.v4i1.6
S. Setiawan, D. Andayani, A. Pudji, L. Soetjiatie, Alievya Brillianty Anugrah Kusuma
The main factor that affects the parameters of the workings of humidity in the baby incubator is the sensor used to read the humidity in the room. The purpose of this study is to analyze the humidity sensor in the baby incubator using 2 humidity sensors (DHT11 and DHT22) in the different location. The manufacture of this device used an after-only design, with a comparison device of INCU Analyzer, DHT11, and DHT22 sensors. Based on the measurement, DHT11 produced a value of 46%, while DHT22 produced a value of 55.45% with BPFK standards of 50%-70%. Based on the results of measurements using the INCU Analyzer, the average error value for DHT11 is 16.05%, while DHT22 is 3.47%. Therefore, the results showed that the DHT22 sensor was more accurate to be used in baby incubators because the measurement results were under BPFK standards and produced a low error value. This can be further implemented in a baby incubator making to improve the health and safety of the babies
影响婴儿恒温箱湿度工作参数的主要因素是用于读取室内湿度的传感器。本研究的目的是利用2个湿度传感器(DHT11和DHT22)在不同位置对婴儿培养箱中的湿度传感器进行分析。本装置的制作采用后置设计,采用INCU分析仪、DHT11、DHT22传感器的比较装置。根据测量,DHT11产生的值为46%,DHT22产生的值为55.45%,BPFK标准为50%-70%。根据INCU分析仪的测量结果,DHT11的平均误差值为16.05%,DHT22的平均误差值为3.47%。因此,结果表明,DHT22传感器测量结果在BPFK标准下,误差值较低,更适合用于婴儿保育箱。这可以在婴儿保温箱制作中进一步实施,以提高婴儿的健康和安全
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引用次数: 0
Artificial Intelligence: A Review of Progress and Prospects in Medicine and Healthcare 人工智能:医学与卫生保健进展与展望综述
Pub Date : 2022-01-16 DOI: 10.35882/jeeemi.v4i1.1
Saurav Mishra
Andrew NG, a leading philosopher in the field of Artificial Intelligence (AI) once quoted “AI is the new electricity” which has the potential to transform and drive every industry. The most important driving factor for the AI transformation will be data. Clive Humby, a data science entrepreneur was once quoted saying “data is the new oil” and data analytics being the “combustion engine” will drive the AI led innovations. The rapid rise of Artificial Intelligence technologies in the past decade, has inspired industries to invest in every opportunity for integrating AI solutions to their products. Research, development, and innovation in the field of AI are shaping various industries like automobile, manufacturing, finance, retail, supply chain management, and education among others. The healthcare industry has also been adopting the ways of AI into various workflows within the domain. With the evolution in computing and processing powers coupled with hardware modernizations, the adoption of AI looks more feasible than ever. Research and Innovations are happening in almost every field of healthcare and hospital workflows with the target of making healthcare processes more efficient & accessible, increase the overall state of healthcare, reduce physician stress levels, and increase the patient satisfaction levels. The conventional ways in which healthcare and clinical workflows have been operating are now starting to see the change with the integration of many data driven AI solutions. The digital innovations are making life easy for healthcare professionals allowing them to spend more time listening to the problems of patients and consequently increasing the patient satisfaction levels. However, there are limitations and concerns on security of Protected Health Information which have to be addressed for a seamless amalgamation of AI systems into the healthcare domain. Many papers have been published which mostly talk about one particular field/problem in the healthcare domain. No publications have covered the opportunities provided by AI technologies to the entire healthcare domain. This review paper discusses in detail about the progress AI has been able to make in the healthcare domain holistically and what the future of AI looks like. The paper also discusses about the implementation opportunities various AI technologies like Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision provide in different fields of healthcare and clinical workflows and how Artificial Intelligence systems will boost the capabilities of healthcare professionals in restoring the human touch in patient-physician encounters. A physician’s intuition and judgement will always remain better suited since each case, each health condition, and each person is unique in its own way, but AI methods can help enhance the accuracy of diagnosis, assist physicians in making improved and precise clinical decisions.
人工智能(AI)领域的著名哲学家吴恩达(Andrew NG)曾说过“人工智能是新的电力”,它有可能改变和推动每一个行业。人工智能转型最重要的驱动因素将是数据。数据科学企业家克莱夫·汉比(Clive Humby)曾说过,“数据是新的石油”,数据分析是“内燃机”,将推动人工智能引领的创新。人工智能技术在过去十年中的迅速崛起,激发了各个行业对将人工智能解决方案集成到其产品中的每一个机会进行投资。人工智能领域的研究、开发和创新正在塑造汽车、制造业、金融、零售、供应链管理、教育等各个行业。医疗保健行业也一直在将人工智能的方式应用到该领域的各种工作流程中。随着计算和处理能力的发展以及硬件的现代化,采用人工智能看起来比以往任何时候都更加可行。医疗保健和医院工作流程的几乎每个领域都在进行研究和创新,其目标是提高医疗保健流程的效率和可访问性,提高医疗保健的整体状态,减少医生的压力水平,并提高患者的满意度。随着许多数据驱动的人工智能解决方案的整合,医疗保健和临床工作流程的传统操作方式现在开始发生变化。数字创新使医疗保健专业人员的生活变得更加轻松,使他们能够花更多的时间倾听患者的问题,从而提高患者的满意度。然而,对于受保护的健康信息的安全性存在限制和担忧,必须解决人工智能系统与医疗保健领域的无缝合并。已经发表的许多论文主要讨论医疗保健领域的一个特定领域/问题。没有出版物涵盖人工智能技术为整个医疗保健领域提供的机会。这篇综述文章详细讨论了人工智能在医疗保健领域所取得的进展,以及人工智能的未来。本文还讨论了各种人工智能技术(如机器学习、深度学习、强化学习、自然语言处理、计算机视觉)在医疗保健和临床工作流程的不同领域提供的实施机会,以及人工智能系统将如何提高医疗保健专业人员在医患接触中恢复人性感的能力。医生的直觉和判断总是更合适,因为每个病例、每个健康状况和每个人都有自己独特的方式,但人工智能方法可以帮助提高诊断的准确性,帮助医生做出改进和精确的临床决策。
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引用次数: 3
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Journal of Electronics, Electromedical Engineering, and Medical Informatics
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