[HTML][HTML] A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities

O Ali, W Abdelbaki, A Shrestha, E Elbasi… - Journal of Innovation & …, 2023 - Elsevier
Administrative and medical processes of the healthcare organizations are rapidly changing
because of the use of artificial intelligence (AI) systems. This change demonstrates the …

[HTML][HTML] Recent advances of artificial intelligence in healthcare: A systematic literature review

F Kitsios, M Kamariotou, AI Syngelakis, MA Talias - Applied Sciences, 2023 - mdpi.com
The implementation of artificial intelligence (AI) is driving significant transformation inside
the administrative and clinical workflows of healthcare organizations at an accelerated rate …

[HTML][HTML] Predicting the onset of diabetes with machine learning methods

CY Chou, DY Hsu, CH Chou - Journal of Personalized Medicine, 2023 - mdpi.com
The number of people suffering from diabetes in Taiwan has continued to rise in recent
years. According to the statistics of the International Diabetes Federation, about 537 million …

A hybrid deep learning technique for personality trait classification from text

H Ahmad, MU Asghar, MZ Asghar, A Khan… - IEEE …, 2021 - ieeexplore.ieee.org
Recently, Cognitive-based Sentiment Analysis with emphasis on automatic detection of user
behaviour, such as personality traits, based on online social media text has gained a lot of …

[HTML][HTML] Data-driven models for atmospheric air temperature forecasting at a continental climate region

MK Alomar, F Khaleel, MM Aljumaily, A Masood… - PLoS …, 2022 - journals.plos.org
Atmospheric air temperature is the most crucial metrological parameter. Despite its influence
on multiple fields such as hydrology, the environment, irrigation, and agriculture, this …

Cardiac Disease Prediction using Supervised Machine Learning Techniques.

C Gupta, A Saha, NVS Reddy… - Journal of Physics …, 2022 - iopscience.iop.org
Diagnosis of cardiac disease requires being more accurate, precise, and reliable. The
number of death cases due to cardiac attacks is increasing exponentially day by day. Thus …

Diagnosis and detection of congenital diseases in new-borns or fetuses using artificial intelligence techniques: a systematic review

K Kaur, C Singh, Y Kumar - Archives of Computational Methods in …, 2023 - Springer
Artificial intelligence, including machine learning and deep learning, play an essential role
in the medical industry for predicting various diseases. One such disease or disorder is a …

[PDF][PDF] A web-based heart disease prediction system using machine learning algorithms

MM Rahman - Network Biology, 2022 - iaees.org
Disease diagnosis is the most critical task in the medical diagnosis system. At present, the
biggest challenge is to predict heart disease very quickly; for that limitation, the number of …

A novel attention-based cross-modal transfer learning framework for predicting cardiovascular disease

NK Karthikeyan - Computers in Biology and Medicine, 2024 - Elsevier
Cardiovascular disease (CVD) remains a leading cause of death globally, presenting
significant challenges in early detection and treatment. The complexity of CVD arises from its …

Heart disease prediction using supervised machine learning algorithms

N Mohan, V Jain, G Agrawal - 2021 5th International …, 2021 - ieeexplore.ieee.org
Predicting and detecting cardiac disease has always been a difficult and time-consuming
undertaking for doctors. To treat cardiac disorders, hospitals and other clinics are giving …