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| Application areas | Strengths | Weaknesses |
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| Cancer | (i) An abundance of molecular assays and data are available for many cancer cases; these can be used towards developing strong decision support systems | (i) More should be done to integrate knowledge from molecular-based and image-based sources available for cancer detection
(ii) There is a need to develop better schemes and methods for validating the effectiveness of the existing and upcoming systems in this area |
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| Radiology | (i) A variety of effective computational techniques exists for many applications in radiology
(ii) It is one of the fastest growing fields using applications of computer-aided decision systems | (i) Most of the research in this area suffers from lack of comprehensive datasets
(ii) Most of these studies do not include knowledge of illness/injury/complication into the decision-making process |
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| Emergency medicine | (i) Although there are only a few systems that have been adopted into clinical practices, the existing systems have shown a positive impact on the cost and quality of healthcare
(ii) There is a significant potential for computer-aided systems in this area since emergency medicine and trauma are very time and resource critical aspects of healthcare | (i) Accuracies of existing systems may not be sufficient for clinical uses
(ii) A variety of illnesses and injuries have not yet been addressed by computer-aided decision support systems
(iii) There is a lack of comprehensive validation of the short-/long-term impacts on these systems using sufficiently large datasets |
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| Cardiovascular medicine | (i) Since heart disease is among the leading causes of death, computer-aided decision systems here have potentially very high impact on world health
(ii) While most cardiovascular-based intelligent decision support systems suffer from high false positives, they often help detect disease at early stages | (i) These systems usually incorporate only a portion of available patient information. More variety in information sources may be required in the decision-making process to reduce false positives
(ii) There is a lack of a comprehensive validation process. Existing research claims need to be tested in more real-world settings |
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| Dental | (i) Existing systems have shown capability for detecting dental complications at early stages
(ii) Such early detection facilitates better practice of preventive care | (i) Some of the technologies used for capturing the information for computer-aided decision support systems are relatively expensive and hence preventing them from being widely adopted in practice |
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