Computational Scientific Discovery in Psychology.

Scientific discovery is a driving force for progress involving creative problem-solving processes to further our understanding of the world. The process of scientific discovery has historically been intensive and time-consuming; however, advances in computational power and algorithms have provided an efficient route to make new discoveries. Complex tools using artificial intelligence (AI) can efficiently analyze data as well as generate new hypotheses and theories. Along with AI becoming increasingly prevalent in our daily lives and the services we access, its application to different scientific domains is becoming more widespread. For example, AI has been used for the early detection of medical conditions, identifying treatments and vaccines (e.g., against COVID-19), and predicting protein structure. The application of AI in psychological science has started to become popular. AI can assist in new discoveries both as a tool that allows more freedom to scientists to generate new theories and by making creative discoveries autonomously. Conversely, psychological concepts such as heuristics have refined and improved artificial systems. With such powerful systems, however, there are key ethical and practical issues to consider. This article addresses the current and future directions of computational scientific discovery generally and its applications in psychological science more specifically.

Undiagnosed Malignancy and Therapeutic Complications in Oncology Patients.

CONTEXT.­: Despite technologic and medical advancements, autopsies are essential to uncover clinically unsuspected diagnoses, to advance our understanding of disease processes, and to help reduce medical errors. OBJECTIVE.­: To investigate the percentage of malignancy clinically diagnosed and undiagnosed in a series of hospital autopsies. Secondarily, to explore the therapeutic complications directly contributing to death in cancer patients. DESIGN.­: A 10-year retrospective study (2008-2018). All nonforensic autopsies performed at the University of Vermont Medical Center during this period were reviewed by 2 pathologists, and data, including antemortem diagnoses of malignancy, and autopsy findings, including therapeutic complications, were collected. RESULTS.­: A total of 246 cases documented a diagnosis of malignancy. In 34.5% (85 of 246) of cases a tissue diagnosis of malignancy was first documented following postmortem examination. In 41.2% (35 of 85) of cases there was clinical antemortem suspicion of malignancy, whereas in 58.8% (50 of 85) clinically unsuspected malignancy was first diagnosed after postmortem examination. In 16.0% (8 of 50) of cases the undiagnosed malignancy was the primary cause of death. The overall rate of therapeutic complication related to the treatment of oncologic disease in patients that resulted in death was 21.7% (35 of 161). CONCLUSIONS.­: Our study shows the percentage of clinically unsuspected malignancies revealed by postmortem examination to be 5% (50 of 1003) of all autopsy cases. In 16% (8 of 50) of cases, the cause of death was due to the clinically undiagnosed malignancy, and hence not to an incidental finding. Despite advances in medical therapy in the management of oncologic disease, in up to 21.7% (35 of 161) of cases therapeutic complications directly contributed to death.

Educational Case: Radiation-Induced Angiosarcoma of the Breast.

The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see http://journals.sagepub.com/doi/10.1177/2374289517715040.1.