A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review

Table 1 Comparative analysis of the review with recent researches

Ref.	Year	Type of Analysis	Focused Research	Lung Disease			Imaging Modality			Detailed Dataset	ML Methods
Ref.	Year	Type of Analysis	Focused Research	Type	S	M	X-ray	CT	O	Detailed Dataset	ML	DL	CNN	TL	EM	O
[13]	2022	Review	Detection	Pneumonia	√	X	√	X	X	X	X	√	√	X	X	~
[14]	2022	Review	Diagnosis	Pneumonia	√	X	√	X	X	X	~	~	~	~	~	~
[15]	2022	Review	Detection and Classification	COVID-19	√	X	√	√	X	X	X	√	√	X	√	~
[16]	2022	Review	Diagnosis	COVID-19	√	X	√	√	√	X	√	√	√	~	~	~
[17]	2022	Survey	Detection and Diagnosis	COVID-19	√	X	√	√	X	~	X	√	√	~	~	~
[18]	2022	Survey	Detection	COVID-19	√	X	~	~	X	X	~	~	~	~	~	~
[19]	2022	Review	Classification	COVID-19	√	X	√	√	X	√	X	√	~	~	~	~
[20]	2022	Review	Prognostication and Detection	Lung Cancer	√	X	X	√	X	X	√	√	~	X	X	X
[21]	2022	Survey	Classification	Lung Cancer	√	X	X	√	X	~	X	X	√	X	X	X
[22]	2023	Review	Detection and Classification	Lung Cancer	√	X	√	√	X	X	X	√	√	X	X	~
This Review	2023	Review	Diagnosis, Detection, Classification, Prediction	Pneumonia COVID-19 Lung Cancer	√	√	√	√	√	√	√	√	√	√	√	√

S Single, M Multiple, O Others, ML Conventional ML Methods Applied, DL DL Methods Applied, CNN Convolutional Neural Network, TL Transfer Learning, EM Ensemble Method, √ Discussed briefly, X Not Discussed, ~ Partially Discussed

ISSN: 1471-2342