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Context: Student assessment is an essential part of higher education. Many different technology-based assessment methods have been formed with the increasing development of IT and its introduction into the education system. Online take-home exams are computer-based exams in which the examinees can take at a place of their own choice and on their own computers. Despite its benefits, this method is faced with certain problems. The present study investigates the challenges in holding take-home computer-based exams in medical sciences and various solutions proposed to use this method more extensively in Iran in situations of crisis. Evidence Acquisition: The present review article was drafted upon a search conducted in Scopus, Google Scholar, and Google’s general search engine using the following keywords and search strategies: "Take-home exam", OR "Take-home assessment", OR, "Online exam", OR "Online assessment", AND "Higher education". The content of the related documents published from 2009 to 2020, including articles, books, and web pages, was selected and assessed, and 35 articles were finally used to accomplish the study objectives. Results: Online take-home exams have many advantages, including reduced human errors, rapid scoring, and reduced stress on the examinees. Nonetheless, one of the limitations of this examination method is that the examinees may not meet all the criteria required for taking exams at home. The obvious risk is students’ unethical conduct and cheating, which composes a major challenge of this examination modality. Conclusions: The reliability and correctness of exams can be improved using combination techniques, question banks, and giving random equivalent questions to each candidate that are not necessarily similar, and also mixing up the questions and their answers, which can provide a tool for preventing or limiting cheating. Online monitoring systems are also one of the strategies proposed for ongoing monitoring of online exams by an invigilator that are generally developed through artificial intelligence.