A low-cost proximate sensing method for early detection of nematodes in walnut using Walabot and scikit-learn classification algorithms

2020 ◽  
Author(s):  
Haoyu Niu ◽  
Tiebiao Zhao ◽  
Andreas Westphal ◽  
YangQuan Chen
Keyword(s):  
Early Detection ◽  
Low Cost ◽  
Classification Algorithms ◽  
Proximate Sensing

Use of RNA isolated from feces as a promising tool for the early detection of colorectal cancer

2012 ◽  
Vol 27 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Giuliano Bernal
Keyword(s):  
Colorectal Cancer ◽  
Early Detection ◽  
Low Cost ◽  
Occult Blood ◽  
Detection Methods ◽  
Fecal Occult Blood ◽  
Public Health Services ◽  
Promising Alternative ◽  
Altered Expression ◽  
Fecal Occult

Colorectal cancer is one of the most common forms of cancer worldwide. Early detection would allow patients to be treated surgically and halt the progression of the disease; however, the current methods of early detection are invasive (colonoscopy and sigmoidoscopy) or have low sensitivity (fecal occult blood test). The altered expression of genes in stool samples of patients with colorectal cancer can be determined by RT-PCR. This is a noninvasive and highly sensitive technique for colorectal cancer screening. According to information gathered in this review and our own experience, the use of fecal RNA to determine early alterations in gene expression due to malignancy appears to be a promising alternative to the current detection methods and owing to its low cost could be implemented in public health services.

scholarly journals Cloud based mobile solution for early detection of Skin Cancer using Artificial Intelligence

2021 ◽  
pp. 312-324
Author(s):  
Pawan Sonawane ◽  
Sahel Shardhul ◽  
Raju Mendhe
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Skin Cancer ◽  
Early Detection ◽  
Transfer Learning ◽  
Network Model ◽  
Neural Network Model ◽  
Mobile Application ◽  
Low Cost ◽  
Skin Tumors

The vast majority of skin cancer deaths are from melanoma, with about 1.04 million cases annually. Early detection of the same can be immensely helpful in order to try to cure it. But most of the diagnosis procedures are either extremely expensive or not available to a vast majority, as these centers are concentrated in urban regions only. Thus, there is a need for an application that can perform a quick, efficient, and low-cost diagnosis. Our solution proposes to build a server less mobile application on the AWS cloud that takes the images of potential skin tumors and classifies it as either Malignant or Benign. The classification would be carried out using a trained Convolution Neural Network model and Transfer learning (Inception v3). Several experiments will be performed based on Morphology and Color of the tumor to identify ideal parameters.

scholarly journals Color Measurement and Analysis of Fruit with a Battery-Less NFC Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1741 ◽  
Author(s):  
Antonio Lazaro ◽  
Marti Boada ◽  
Ramon Villarino ◽  
David Girbau
Keyword(s):  
Low Cost ◽  
Near Field ◽  
Color Space ◽  
Cloud Service ◽  
Color Measurement ◽  
Classification Algorithms ◽  
Measurement And Analysis ◽  
Hue Angle ◽  
Color Data ◽  
The Magnetic Field

This paper presents a color-based classification system for grading the ripeness of fruit using a battery-less Near Field Communication (NFC) tag. The tag consists of a color sensor connected to a low-power microcontroller that is connected to an NFC chip. The tag is powered by the energy harvested from the magnetic field generated by a commercial smartphone used as a reader. The raw RGB color data measured by the colorimeter is converted to HSV (hue, saturation, value) color space. The hue angle and saturation are used as features for classification. Different classification algorithms are compared for classifying the ripeness of different fruits in order to show the robustness of the system. The low cost of NFC chips means that tags with sensing capability can be manufactured economically. In addition, nowadays, most commercial smartphones have NFC capability and thus a specific reader is not necessary. The measurement of different samples obtained on different days is used to train the classification algorithms. The results of training the classifiers have been saved to the cloud. A mobile application has been developed for the prediction based on a table-based method, where the boundary decision is downloaded from a cloud service for each product. High accuracy, between 80 and 93%, is obtained depending on the kind of fruit and the algorithm used.

scholarly journals A Low-cost Biomarker-based SAW-Biosensor Design for Early Detection of Prostate Cancer

2017 ◽  
Vol 27 ◽  
pp. 248-249 ◽  
Author(s):  
Alper Sisman ◽  
Etki Gur ◽  
Sencer Ozturk ◽  
Burak Enez ◽  
Bilal Okur ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Early Detection ◽  
Low Cost

Coorscreen: A Low-Cost, on-Site Mammography Screening Program

1996 ◽  
Vol 10 (5) ◽  
pp. 364-370 ◽  
Author(s):  
Mary Greenwood ◽  
Joanne Henritze
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Malignant Disease ◽  
Screening Program ◽  
Low Cost ◽  
Cost Savings ◽  
Participation Rate ◽  
Program Cost ◽  
Mammography Screening Program ◽  
Screening And Prevention

Setting. Coors Brewing Company is a self-insured corporation of 10,600 employees located in Golden, Colorado. Management has long believed in the value of a healthy workforce and has instituted ongoing health and wellness programming since 1981. Program design. Coorscreen was started in September 1985 to create an ongoing awareness of breast cancer screening and prevention for all female employees, spouses, and retirees and to lower the health care costs for the company through early detection of breast cancer. Program impact. From 1985 through 1993, 12,210 mammograms were completed on 3729 employees, spouses, and retirees. The participation rate was 83%. Forty-seven malignant conditions were confirmed during the first 8 years. Pathology reports confirmed 43 early detections (10 employees) and four late detections (two employees). The 10 cases of malignant disease detected early among employees cost an average of $12,388 in terms of direct medical costs, short-term disability, temporary replacement, and ongoing benefits. The two cases detected late among employees cost an average of $143,398. Among spouses, cases of malignant disease detected late have cost an average of $69,230 more than cases detected early. On the basis of early detection for 10 employees and 26 spouses, the total savings are estimated to be $3,110,000. Discussion. The Coorscreen program cost savings for the first 8 years were $3,110,080 because of the lower cost of early versus late detection. Total screening and procedural costs to the company have equaled $668,690. Thus the company has realized a total cost savings of $2,441,190.

scholarly journals Early Detection of Atrial Fibrillation Based on ECG Signals

2020 ◽  
Vol 7 (1) ◽  
pp. 16
Author(s):  
Nuzhat Ahmed ◽  
Yong Zhu
Keyword(s):  
Atrial Fibrillation ◽  
Early Detection ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Research Work ◽  
Threshold Values ◽  
Heart Health ◽  
Ecg Signals ◽  
Normal Heart Rate

Atrial fibrillation, often called AF is considered to be the most common type of cardiac arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate treatment is crucial if the symptoms seem to be consistent and persistent. This research work focused on the development of a heart monitoring system which could be considered as a feasible solution in early detection of potential AF in real time. The objective was to bridge the gap in the market for a low-cost, at home use, noninvasive heart health monitoring system specifically designed to periodically monitor heart health in subjects with AF disorder concerns. The main characteristic of AF disorder is the considerably higher heartbeat and the varying period between observed R waves in electrocardiogram (ECG) signals. This proposed research was conducted to develop a low cost and easy to use device that measures and analyzes the heartbeat variations, varying time period between successive R peaks of the ECG signal and compares the result with the normal heart rate and RR intervals. Upon exceeding the threshold values, this device creates an alert to notify about the possible AF detection. The prototype for this research consisted of a Bitalino ECG sensor and electrodes, an Arduino microcontroller, and a simple circuit. The data was acquired and analyzed using the Arduino software in real time. The prototype was used to analyze healthy ECG data and using the MIT-BIH database the real AF patient data was analyzed, and reasonable threshold values were found, which yielded a reasonable success rate of AF detection.

scholarly journals Electrochemistry-based approaches to low cost, high sensitivity, automated, multiplexed protein immunoassays for cancer diagnostics

The Analyst ◽  
2016 ◽  
Vol 141 (2) ◽  
pp. 536-547 ◽  
Author(s):  
Chandra K. Dixit ◽  
Karteek Kadimisetty ◽  
Brunah A. Otieno ◽  
Chi Tang ◽  
Spundana Malla ◽  
...  
Keyword(s):  
Early Detection ◽  
Low Cost ◽  
High Sensitivity ◽  
Cancer Diagnostics ◽  
Cancer Therapies

Early detection and reliable diagnostics are keys to effectively design cancer therapies with better prognoses.

Sign in / Sign up

Export Citation Format

Share Document