You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

The Use of a Software - Assisted Method to Estimate Fetal Weight at and Near Term Using Magnetic Resonance Imaging The aim of this study was to apply a semi-automated calculation method of fetal body volume and, thus, of magnetic resonance-estimated fetal weight (MR-EFW) prior to planned delivery and to evaluate whether the technique of measurement could be simplified while remaining accurate. MR-EFW was calculated using a semi-automated method at 38.6 weeks of gestation in 36 patients and compared to the picture archiving and communication system (PACS). Per patient, 8 sequences were acquired with a slice thickness of 4-8 mm and an intersection gap of 0, 4, 8, 12, 16, or 20 mm. The median absolute relative errors for MR-EFW and the time of planimetric measurements were calculated for all 8 sequences and for each method (assisted vs. PACS), and the difference between the methods was calculated. The median delivery weight was 3,280 g. The overall median relative error for all 288 MR-EFW calculations was 2.4% using the semi-automated method and 2.2% for the PACS method. Measurements did not differ between the 8 sequences using the assisted method (p = 0.313) or the PACS (p = 0.118), while the time of planimetric measurement decreased significantly with a larger gap (p < 0.001) and in the assisted method compared to the PACS method (p < 0.01). Our simplified MR-EFW measurement showed a dramatic decrease in time of planimetric measurement without a decrease in the accuracy of weight estimates.
{"AnatomicalStructure": ["fetal"], "Bacterium": [], "BiologicFunction": ["gestation", "delivery", "Term"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": [], "Food": [], "HealthCareActivity": ["Magnetic Resonance Imaging", "evaluate"], "InjuryOrPoisoning": [], "IntellectualProduct": ["Software", "method", "methods", "Method"], "MedicalDevice": ["picture archiving and communication system", "PACS"], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study"], "SpatialConcept": ["intersection gap", "gap", "median"], "Virus": []}