[Retracted] Efficient Prediction of Missed Clinical Appointment Using Machine Learning

Table 2

Useful features.

Name	Type	Range	Description
Date of birth	Input	mm/dd/yyyy	Date of birth of patient
Race	Input	Like Asian, African, white	Race of patient
Sex	Input	Male/female/other	Sex of patient
Civil status	Input	Single, married, divorced, separated, widowed	Civil status
Admit	Input	Textual format	Reason of admission
Date of appointment	Input	mm/dd/yyyy date	Date of appointment
Status of appointment	Input	Pending, closed, canceled	Status of appointment
Cancel date	Input	mm/dd/yyyy date	Canceling appointment date
Cancel reason	Input	No-show-up, death, rescheduled, out of city	Canceling appointment reason
Create time	Input	Time stamp format	Time at which database entry record was inserted
Modified time	Input	Time stamp format	Time at which database entry record was modified
Procedure type	Input	Like ultrasound, office visit see table	In which procedure patient booked appointment
Patient age	Generated	Numeric	Created by date of birth
Age range	Generated	From age category	Created by patient age feature
Create Appt difference	Generated	No of days	Created by taking difference of appointment date and create time
Appointment season	Generated	Month of year	Created with the help of appointment date
Cancel difference	Generated	No. of days	Created by taking difference of cancel date and appointment date