A computer-aided diagnosis, CAD, apparatus comprising: a memory configured to store instructions therein; and at least one processor, upon execution of the instructions, configured to: extract a lesion feature value from a captured lesion image; receive at least one additional information; and diagnose the lesion based on a combination of the extracted lesion feature value and the received additional information, wherein the processor, upon execution of the instructions, is further configured to: compare the extracted lesion feature value and the received additional information with a lesion diagnosis model; and diagnose the lesion based on a result of the comparing. wherein the CAD apparatus further comprises a user interface configured to receive the additional information from a user; and the user interface comprises: a lesion image display area configured to display the captured lesion image; and an additional information input area configured to receive the additional information from the user; wherein the additional information input area is further configured to: display one or more additional information fields for selection by a user; and in response to one of the additional information fields being selected by the user, display one or more sub-fields of the selected additional information field; wherein the CAD apparatus is configured to calculate the likelihood that each of the sub-fields of the additional information field is a correct representation of the lesion by comparing a lesion feature value associated with the additional information field of the lesion and extracted by the lesion feature extractor with the lesion diagnosis model, and to display the sub-fields of the additional information field in order of the likelihood that the sub-fields are a correct representation of the lesion based on the results of the calculation. a memory configured to store instructions therein; and at least one processor, upon execution of the instructions, configured to: extract a lesion feature value from a captured lesion image; receive at least one additional information; and diagnose the lesion based on a combination of the extracted lesion feature value and the received additional information, extract a lesion feature value from a captured lesion image; receive at least one additional information; and diagnose the lesion based on a combination of the extracted lesion feature value and the received additional information, wherein the processor, upon execution of the instructions, is further configured to: compare the extracted lesion feature value and the received additional information with a lesion diagnosis model; and diagnose the lesion based on a result of the comparing. compare the extracted lesion feature value and the received additional information with a lesion diagnosis model; and diagnose the lesion based on a result of the comparing. wherein the CAD apparatus further comprises a user interface configured to receive the additional information from a user; and the user interface comprises: a lesion image display area configured to display the captured lesion image; and an additional information input area configured to receive the additional information from the user; a lesion image display area configured to display the captured lesion image; and an additional information input area configured to receive the additional information from the user; wherein the additional information input area is further configured to: display one or more additional information fields for selection by a user; and in response to one of the additional information fields being selected by the user, display one or more sub-fields of the selected additional information field; display one or more additional information fields for selection by a user; and in response to one of the additional information fields being selected by the user, display one or more sub-fields of the selected additional information field; wherein the CAD apparatus is configured to calculate the likelihood that each of the sub-fields of the additional information field is a correct representation of the lesion by comparing a lesion feature value associated with the additional information field of the lesion and extracted by the lesion feature extractor with the lesion diagnosis model, and to display the sub-fields of the additional information field in order of the likelihood that the sub-fields are a correct representation of the lesion based on the results of the calculation.