# A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence
## 2 Overview of Healthcare Applications
### mHealth  
In many fields, predicting a health crisis has long been limited to the classic method of collecting useful information from patients. These methods imply direct contact with the patient for a significant amount of time, either in person or by video calls. Newer and smarter technologies allow clinicians and researchers to collect data about the patient's everyday activities through noninvasive methods by continuously gathering sensor data from devices such as smartphones, smartwatches and other personal gadgets. By analyzing this information, the emergence of specific patterns can be observed and then correlated to different health events. One such use of passively collected data to determine biomarkers for mood states can be seen in [29], where emotional state prediction models were tested for clinical outpatients that had previously been diagnosed with mental disorders, owned smartphones with \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Authors** & **Work Description** & **Results** & **Technologies Employed** \\ \hline \multirow{4}{*}{[23]} & A blockchain-based system & The system does not upload medical records but & \multirow{2}{*}{Blockchain, mobile app} \\  & for detecting medical & notifies the patients if the documents have been & \\  & document changes and & changed. & \\  & notifying patients & & \\ \hline \multirow{4}{*}{[24]} & Fuzzy-based trust & \multirow{2}{*}{Proposed model recognizes compromised Sybil} & \multirow{2}{*}{Internet of Medical Things} \\  & management for preventing & & nodes and declares them malicious; Sybil attacks are & \\  & Sybil attacks on Internet of & difficult to detect. & \\  & Medical Things systems & & \\ \hline \multirow{4}{*}{[25]} & Personal health assistant & System with conversational agent that monitors & \multirow{2}{*}{\begin{tabular}{c} Artificial \\ intelligence/machine learning, \\ chatbot, Telegram-based \\ \end{tabular} } \\  & using the Italian language & & suggest doctors; the generated probability dataset & \\  & can be used for 217 diseases. & & \\ \hline \multirow{4}{*}{[26]} & IoT-based eHealth & Using geographic routing algorithms to monitor & \multirow{2}{*}{GPS, Node-RED, Influx,} \\  & surveillance system designed & persons for health conditions, social distancing, and & \\  & for pandemics & mask-wearing status. & \\ \hline \multirow{4}{*}{[27]} & A system for analyzing and & \multirow{2}{*}{\
\begin{tabular}{c} Tested prediction results on real hospital data \\ collected from 500 patients presenting risk factors of \\ developing diabetes mellitus. \\ \end{tabular} } \\  & & & intelligence/machine learning, \\ \hline \multirow{4}{*}{[28]} & \multirow{4}{*}{LI-Care system for health } & Cost-efficient monitoring system with GUI offering & \multirow{2}{*}{
\begin{tabular}{c} LabView, IoT, National \\ Instruments myRIO-1900 \\ \end{tabular} } \\  & & powerful signal acquisition and processing; data & \\ \cline{1-1}  & monitoring & rates of the sensors used in this work are between & \\ \cline{1-1}  & & 120 B/s and 10 KB/s. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont. Android or iOS operating systems, and had them connected to Wi-Fi networks at least a couple of times per week. Cardiac monitoring wearable implementations can offer a wide range of applications, often targeting similar types of biomedical data. Standard electrocardiogram (ECG) measurements offer glimpses of electrical signals over a short period of time and any arrhythmia that occurs outside that time interval is overlooked. A solution to this problem is a continuous ECG monitoring system that is not prone to overlook certain episodes. There are multiple types of cardiac monitoring, as stated in [30], where different aspects are discussed:  
1. Advantages and disadvantages of wearable solutions for arrhythmia monitoring (outpatient telemetry);
2. Wearables can also deliver therapy (electric shocks in life-threatening situations);
3. they can improve the quality of life (early discharge, less outpatient visits, reassurances);
4.