TY - JOUR
TI - Nano simply alpha open set and novel neighborhood techniques for accurate symptom detection in medical applications
AU - El Sayed M
JN - Thermal Science
PY - 2024
VL - 28
IS - 6
SP - 5125
EP - 5141
PT - Article
AB - This study introduces the nano simply alpha open set and proposes a new  approximation space extending Pawlak's approximation. This new space  includes the nano simply alpha lower and nano simply alpha upper  approximations, denoted by specific notations, offering a refined framework  for analyzing data. The ζ nα-lower and ζ nα-upper approximations for any set  Also, we study nano ζ nα-rough approximation. Those investigations look at  the connections between various approximation types and their  characteristics, proposing methods applicable to medical diagnosis and other  decision-making fields. These methods provide deeper data insights,  enhancing precision and reliability in complex problem-solving. We  introduce a "general neighborhood" concept, expanding on Pawlak space with  a general upper and lower approximation. A case study for chronic kidney  disease demonstrates the effectiveness of these methods in identifying  critical symptoms. Additionally, an algorithm a, supports application for  any number of patients or decision-making issues.