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Field data forecasting using lstm and bi-lstm approaches
(
MDPI
, 2021 , Article)
Water, an essential resource for crop production, is becoming increasingly scarce, while cropland continues to expand due to the world's population growth. Proper irrigation scheduling has been shown to help farmers improve ...
Estimating blood pressure from the photoplethysmogram signal and demographic features using machine learning techniques
(
MDPI AG
, 2020 , Article)
Hypertension is a potentially unsafe health ailment, which can be indicated directly from the blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; ...
A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations
(
Elsevier
, 2021 , Article)
Background: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques ...
An investigation to study the effects of Tai Chi on human gait dynamics using classical machine learning
(
Elsevier
, 2022 , Article)
Tai Chi has been proven effective in preventing falls in older adults, improving the joint function of knee osteoarthritis patients, and improving the balance of stroke survivors. However, the effect of Tai Chi on human ...
Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques
(
MDPI
, 2022 , Article)
Diabetes mellitus (DM) can lead to plantar ulcers, amputation and death. Plantar foot thermogram images acquired using an infrared camera have been shown to detect changes in temperature distribution associated with a ...
Performance analysis of conventional machine learning algorithms for diabetic sensorimotor polyneuropathy severity classification
(
MDPI
, 2021 , Article)
Background: Diabetic peripheral neuropathy (DSPN), a major form of diabetic neuropathy, is a complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis ...
Analysis of customers' satisfaction with baby products: The moderating role of brand image
(
Elsevier
, 2023 , Article)
The previous experience of customers is assessed by textual reviews and ratings to reflect their levels of satisfaction with the service or product. Online reviews and ratings have played a vital role to assess the performance ...
Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions
(
Elsevier
, 2023 , Article)
Artificial intelligence (AI) is a set of rapidly expanding disruptive technologies that are radically transforming various aspects related to people, business, society, and the environment. With the proliferation of digital ...
Modeling of forward osmosis process using artificial neural networks (ANN) to predict the permeate flux
(
Elsevier
, 2020 , Article)
Artificial neural networks (ANN) are black box models that are becoming more popular than transport-based models due to their high accuracy and less computational time in predictions. The literature shows a lack of ANN ...
Netizens' behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach
(
Emerald Publishing
, 2021 , Article)
Purpose: Based on the concepts confined in Ajzen's theory of planned behavior (TPB), this study investigates users' attitudes towards adoption of a blockchain-based framework in the esports industry that proposes a scheme ...