-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathdatatype_dictionary.json
205 lines (205 loc) · 8.84 KB
/
datatype_dictionary.json
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
{
"datatype": [
{
"code_name": "clinical_data",
"datatype_description": {
"description_text": "All clinical data (survey responses, blood/urine test results, etc.). Typically collected through REDCap.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": ["redcap_data"],
"related_terms": {
"ncit": ["C15783"]
},
"related_standards": [
{
"standard_name": "The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM)",
"standard_reference": "https://www.ohdsi.org/data-standardization/",
"standard_description": "Data standard designed to standardize the structure and content of observational data and to enable efficient analyses that can produce reliable evidence."
}
]
},
{
"code_name": "ekg",
"datatype_description": {
"description_text": "Recording of the moment-to-moment electromotive forces of the heart as projected onto various sites on the body's surface, delineated as a scalar function of time. The recording is monitored by a tracing on slow moving chart paper or by observing it on a cardioscope, which is a cathode ray tube display.",
"description_source": {
"resource": {
"resource_name": "Medical Subject Headings (MeSH)",
"resource_links": ["https://meshb.nlm.nih.gov/record/ui?ui=D004562"]
}
}
},
"aliases": [
"ecg",
"electrocardiogram",
"electrocardiography",
"ekg_data",
"ecg_data",
"electrocardiogram_data",
"electrocardiography_data",
"ekg_measurements",
"ecg_measurements",
"electrocardiogram_measurements",
"electrocardiography_measurements"
],
"related_terms": {
"ncit": ["C168186"],
"mesh": ["D004562"]
}
},
{
"code_name": "eye_fundus_photography",
"datatype_description": {
"description_text": "Data collected using a fundus camera to record color images of the condition of the interior surface of the eye.",
"description_source": {
"resource": {
"resource_name": "AI-READI Consortium",
"resource_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"eye_fundus_photography_data",
"eye_fundus_photography_images",
"color_fundus_retinal_photography",
"color_fundus_retinal_photography_data",
"color_fundus_retinal_photography_images",
],
"related_terms": {
"ncit": ["C147467"]
}
},
{
"code_name": "oct",
"datatype_description": {
"description_text": "Data collected using optical coherence tomography (OCT), an imaging method using lasers that is used for mapping subsurface structure.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"optical_coherence_tomography",
"oct_data",
"optical_coherence_tomography_data",
"oct_images",
"optical_coherence_tomography_images"
],
"related_terms": {
"ncit": ["C20828"],
"mesh": ["D041623"]
},
"related_standards": [
{
"standard_name": "Digital Imaging and Communications in Medicine (DICOM)",
"standard_reference": "https://dicom.nema.org/medical/dicom/2020b/output/chtml/part03/sect_C.8.17.14.html",
"standard_description": "Standard for the digital storage and transmission of medical images and related information"
}
]
},
{
"code_name": "octa",
"datatype_description": {
"description_text": "Data collected using optical coherence tomography angiography (OCTA), a non-invasive imaging technique that generates volumetric angiography images.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"optical_coherence_tomography_angiography",
"octa_data",
"optical_coherence_tomography_angiography_data",
"octa_images",
"optical_coherence_tomography_angiography_images"
],
"related_standards": [
{
"standard_name": "Digital Imaging and Communications in Medicine (DICOM)",
"standard_reference": "https://www.dicomstandard.org/news/supplements/view/ophthalmic-tomography-angiographic-(oct-a)-image-storage-sop-classes",
"standard_description": "Standard for the digital storage and transmission of medical images and related information"
}
]
},
{
"code_name": "flio",
"datatype_description": {
"description_text": "Data collected through fluorescence lifetime imaging ophthalmoscopy (FLIO), an imaging modality for in vivo measurement of lifetimes of endogenous retinal fluorophores.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"flio_data",
"flio_images",
"fluorescence_lifetime_imaging_ophthalmoscopy_data",
"fluorescence_lifetime_imaging_ophthalmoscopy_images"
]
},
{
"code_name": "continuous_glucose_monitoring",
"datatype_description": {
"description_text": "Data collected through continuous glucose monitoring device.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"continuous_glucose_monitoring_data",
"continuous_glucose_monitoring_measurements"
],
"related_terms": {
"ncit": ["C159776"]
}
},
{
"code_name": "activity_monitoring",
"datatype_description": {
"description_text": "Data collected through an activity monitoring device such as Fitbit, Apple Watch, etc.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"phyisical_activity_monitoring",
"activity_monitoring_data",
"phyisical_activity_monitoring_data",
"activity_monitoring_measurements",
"phyisical_activity_monitoring_measurements"
]
},
{
"code_name": "environmental_sensor_measurements",
"datatype_description": {
"description_text": "Data collected through environmental sensor device. Typically measures of air quality, light intensity, etc.",
"description_source": {
"organization": {
"organization_name": "AI-READI Consortium",
"organization_links": ["https://aireadi.org/"]
}
}
},
"aliases": [
"environmental_sensor_measurements_data"
]
}
]
}