Datasets:
Tasks:
Tabular Classification
Formats:
csv
Languages:
English
Size:
10K - 100K
Tags:
digital-health
artificial-intelligence
clinical-decision-support
CDSS
Synthetic
sub-saharan-africa
License:
id int64 | facility_level string | location string | internet_available int64 | power_reliable int64 | smartphone_available int64 | ai_tool_available int64 | cdss_available int64 | ai_domain string | ai_type string | deployment_mode string | open_source int64 | regulatory_approved int64 | validated_local_population int64 | ai_used_this_encounter int64 | recommendation_generated int64 | recommendation_followed int64 | recommendation_overridden int64 | override_reason string | diagnostic_accuracy_improved int64 | time_saved_minutes int64 | patient_outcome_improved int64 | false_positive int64 | false_negative int64 | provider_trust_ai int64 | training_received int64 | ease_of_use_score int64 | barrier_infrastructure int64 | barrier_trust int64 | barrier_training int64 | barrier_regulation int64 | barrier_data_quality int64 | barrier_cost int64 | barrier_bias_concern int64 | year int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | clinic | peri_urban | 0 | 0 | 1 | 0 | 0 | malaria_microscopy | image_recognition | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,023 |
2 | district | remote | 0 | 0 | 1 | 0 | 0 | tb_xray_screening | rule_based | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 6 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 2,023 |
3 | health_centre | peri_urban | 0 | 0 | 1 | 0 | 0 | tb_xray_screening | image_recognition | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,022 |
4 | clinic | rural | 0 | 0 | 1 | 0 | 0 | diabetic_retinopathy | predictive_model | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,020 |
5 | tertiary | urban | 0 | 1 | 1 | 0 | 0 | maternal_risk | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2,023 |
6 | health_centre | peri_urban | 1 | 1 | 0 | 0 | 0 | dermatology | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 4 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 2,022 |
7 | district | urban | 1 | 0 | 1 | 0 | 0 | dermatology | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,021 |
8 | health_centre | peri_urban | 1 | 0 | 0 | 0 | 0 | tb_xray_screening | rule_based | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 2,023 |
9 | district | remote | 0 | 0 | 1 | 0 | 0 | tb_xray_screening | predictive_model | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 2,023 |
10 | district | remote | 0 | 1 | 0 | 0 | 0 | drug_interaction | hybrid | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 2,022 |
11 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | tb_xray_screening | hybrid | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 3 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 2,020 |
12 | district | remote | 0 | 0 | 0 | 0 | 0 | tb_xray_screening | image_recognition | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 2 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,021 |
13 | district | rural | 0 | 1 | 1 | 0 | 0 | ecg_interpretation | nlp | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 2,023 |
14 | district | peri_urban | 0 | 0 | 0 | 0 | 0 | diabetic_retinopathy | image_recognition | edge_device | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2,023 |
15 | clinic | rural | 0 | 1 | 0 | 0 | 0 | triage_severity | nlp | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 7 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 2,021 |
16 | community | remote | 0 | 0 | 0 | 0 | 0 | ecg_interpretation | predictive_model | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 2,020 |
17 | community | remote | 0 | 0 | 0 | 0 | 0 | drug_interaction | image_recognition | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,020 |
18 | regional | urban | 1 | 1 | 0 | 0 | 0 | clinical_guidelines | rule_based | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 5 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
19 | health_centre | peri_urban | 0 | 0 | 0 | 0 | 0 | maternal_risk | image_recognition | edge_device | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,020 |
20 | community | remote | 0 | 0 | 1 | 0 | 0 | maternal_risk | image_recognition | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 5 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 2,022 |
21 | clinic | urban | 0 | 1 | 0 | 0 | 0 | maternal_risk | rule_based | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 4 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 2,023 |
22 | community | rural | 1 | 0 | 1 | 0 | 0 | tb_xray_screening | image_recognition | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 2,022 |
23 | community | urban | 0 | 1 | 1 | 0 | 0 | diabetic_retinopathy | nlp | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,021 |
24 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | drug_interaction | predictive_model | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 5 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,022 |
25 | regional | urban | 0 | 1 | 1 | 0 | 0 | dermatology | rule_based | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 2,021 |
26 | health_centre | rural | 0 | 0 | 1 | 0 | 0 | tb_xray_screening | image_recognition | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 3 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,022 |
27 | regional | urban | 0 | 1 | 1 | 0 | 0 | drug_interaction | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2,023 |
28 | health_centre | remote | 0 | 0 | 0 | 0 | 0 | dermatology | predictive_model | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,021 |
29 | health_centre | urban | 0 | 0 | 1 | 0 | 0 | triage_severity | rule_based | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 5 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
30 | district | rural | 0 | 0 | 1 | 0 | 0 | triage_severity | hybrid | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2,019 |
31 | regional | rural | 0 | 0 | 0 | 0 | 0 | tb_xray_screening | image_recognition | offline | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,021 |
32 | clinic | peri_urban | 0 | 1 | 1 | 0 | 0 | tb_xray_screening | nlp | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
33 | health_centre | urban | 0 | 1 | 1 | 1 | 0 | maternal_risk | nlp | cloud | 0 | 0 | 0 | 1 | 0 | 0 | 0 | na | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 2,021 |
34 | health_centre | remote | 0 | 0 | 0 | 0 | 0 | ecg_interpretation | hybrid | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 3 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 2,019 |
35 | district | urban | 0 | 1 | 1 | 0 | 0 | pathology | image_recognition | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 2,021 |
36 | district | remote | 0 | 1 | 1 | 0 | 0 | maternal_risk | image_recognition | edge_device | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 2,019 |
37 | regional | rural | 1 | 0 | 0 | 0 | 1 | clinical_guidelines | rule_based | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
38 | health_centre | urban | 0 | 1 | 1 | 0 | 0 | tb_xray_screening | image_recognition | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 6 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 2,023 |
39 | tertiary | urban | 0 | 0 | 1 | 0 | 0 | triage_severity | rule_based | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 2,022 |
40 | health_centre | peri_urban | 0 | 0 | 1 | 0 | 0 | pathology | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 2,021 |
41 | clinic | remote | 0 | 0 | 0 | 0 | 0 | triage_severity | rule_based | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 2,023 |
42 | district | rural | 0 | 0 | 1 | 0 | 0 | pathology | rule_based | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 4 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 2,020 |
43 | clinic | remote | 0 | 1 | 1 | 0 | 0 | diabetic_retinopathy | image_recognition | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
44 | community | urban | 1 | 1 | 1 | 0 | 0 | drug_interaction | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,021 |
45 | community | urban | 0 | 1 | 1 | 0 | 0 | pathology | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 6 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2,022 |
46 | health_centre | rural | 0 | 0 | 1 | 0 | 0 | triage_severity | hybrid | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2,022 |
47 | regional | remote | 0 | 0 | 0 | 0 | 0 | dermatology | image_recognition | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 7 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,021 |
48 | tertiary | rural | 1 | 1 | 0 | 0 | 0 | dermatology | rule_based | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 2,023 |
49 | health_centre | remote | 0 | 0 | 1 | 0 | 0 | malaria_microscopy | predictive_model | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 2,023 |
50 | health_centre | rural | 1 | 0 | 1 | 0 | 0 | diabetic_retinopathy | rule_based | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,021 |
51 | health_centre | peri_urban | 0 | 1 | 0 | 1 | 0 | clinical_guidelines | rule_based | cloud | 0 | 0 | 0 | 1 | 1 | 0 | 1 | clinical_judgment | 0 | 12 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,021 |
52 | health_centre | peri_urban | 1 | 0 | 0 | 0 | 1 | dermatology | rule_based | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 2,023 |
53 | tertiary | urban | 0 | 1 | 0 | 0 | 0 | ecg_interpretation | image_recognition | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 2 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,021 |
54 | health_centre | peri_urban | 1 | 0 | 1 | 0 | 0 | ecg_interpretation | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 2,020 |
55 | tertiary | peri_urban | 0 | 1 | 0 | 0 | 0 | tb_xray_screening | hybrid | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 6 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,021 |
56 | district | urban | 0 | 1 | 1 | 0 | 0 | ecg_interpretation | nlp | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 2,021 |
57 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | drug_interaction | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,020 |
58 | tertiary | urban | 0 | 0 | 1 | 0 | 0 | triage_severity | hybrid | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 6 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 2,023 |
59 | district | peri_urban | 1 | 1 | 1 | 0 | 0 | clinical_guidelines | hybrid | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 6 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 2,022 |
60 | district | remote | 0 | 0 | 1 | 0 | 0 | triage_severity | hybrid | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 5 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 2,022 |
61 | health_centre | remote | 0 | 0 | 1 | 0 | 0 | triage_severity | rule_based | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,021 |
62 | clinic | remote | 0 | 0 | 1 | 0 | 0 | clinical_guidelines | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 6 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2,021 |
63 | clinic | peri_urban | 0 | 1 | 1 | 0 | 0 | triage_severity | hybrid | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,022 |
64 | district | peri_urban | 1 | 0 | 0 | 0 | 0 | clinical_guidelines | image_recognition | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 3 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 2,020 |
65 | regional | peri_urban | 1 | 0 | 1 | 0 | 0 | tb_xray_screening | rule_based | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2,023 |
66 | tertiary | remote | 0 | 1 | 1 | 0 | 0 | triage_severity | hybrid | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 5 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 2,023 |
67 | clinic | remote | 0 | 0 | 1 | 0 | 0 | drug_interaction | hybrid | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,023 |
68 | health_centre | urban | 1 | 1 | 0 | 0 | 0 | clinical_guidelines | hybrid | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 2,022 |
69 | clinic | remote | 0 | 1 | 1 | 0 | 0 | pathology | rule_based | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 5 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 2,020 |
70 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | triage_severity | image_recognition | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 7 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 2,023 |
71 | district | rural | 0 | 0 | 1 | 0 | 0 | other | nlp | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,023 |
72 | district | urban | 0 | 1 | 1 | 0 | 0 | clinical_guidelines | rule_based | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 1 | 0 | 1 | 1 | 0 | 0 | 1 | 2,022 |
73 | clinic | rural | 0 | 0 | 0 | 0 | 0 | tb_xray_screening | predictive_model | edge_device | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 7 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,023 |
74 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | malaria_microscopy | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 4 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 2,023 |
75 | community | remote | 0 | 0 | 0 | 0 | 0 | clinical_guidelines | nlp | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 2 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 2,023 |
76 | district | remote | 1 | 0 | 0 | 0 | 0 | other | image_recognition | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 2,019 |
77 | district | rural | 0 | 1 | 0 | 0 | 0 | diabetic_retinopathy | image_recognition | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,023 |
78 | regional | rural | 1 | 1 | 0 | 0 | 0 | clinical_guidelines | rule_based | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 5 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 2,022 |
79 | clinic | urban | 0 | 0 | 0 | 0 | 0 | clinical_guidelines | nlp | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
80 | district | urban | 1 | 1 | 1 | 0 | 0 | malaria_microscopy | hybrid | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,022 |
81 | health_centre | remote | 1 | 0 | 0 | 0 | 0 | pathology | hybrid | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 2,022 |
82 | tertiary | peri_urban | 0 | 1 | 1 | 0 | 1 | malaria_microscopy | image_recognition | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,022 |
83 | health_centre | rural | 0 | 0 | 0 | 0 | 0 | ecg_interpretation | nlp | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2,023 |
84 | tertiary | urban | 0 | 0 | 0 | 0 | 0 | maternal_risk | predictive_model | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 2,023 |
85 | clinic | urban | 0 | 1 | 1 | 0 | 0 | dermatology | predictive_model | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 8 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,022 |
86 | regional | urban | 1 | 0 | 1 | 0 | 0 | malaria_microscopy | predictive_model | edge_device | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 2,022 |
87 | health_centre | remote | 0 | 1 | 1 | 0 | 1 | triage_severity | rule_based | offline | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2,021 |
88 | community | rural | 0 | 0 | 0 | 0 | 0 | diabetic_retinopathy | image_recognition | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 2,022 |
89 | community | remote | 0 | 0 | 1 | 0 | 0 | drug_interaction | predictive_model | offline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 4 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 2,022 |
90 | tertiary | peri_urban | 1 | 0 | 1 | 0 | 1 | drug_interaction | image_recognition | hybrid | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 6 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 2,022 |
91 | regional | urban | 1 | 0 | 1 | 0 | 0 | dermatology | predictive_model | cloud | 1 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2,023 |
92 | regional | rural | 0 | 1 | 1 | 0 | 0 | pathology | image_recognition | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 5 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 2,023 |
93 | health_centre | urban | 0 | 0 | 1 | 0 | 0 | tb_xray_screening | rule_based | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 2,022 |
94 | community | rural | 0 | 0 | 0 | 0 | 0 | drug_interaction | hybrid | cloud | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 3 | 1 | 2 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 2,021 |
95 | clinic | rural | 0 | 0 | 0 | 0 | 0 | clinical_guidelines | predictive_model | cloud | 1 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 3 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 2,022 |
96 | district | rural | 1 | 1 | 1 | 0 | 0 | ecg_interpretation | nlp | edge_device | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 2 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 2,023 |
97 | district | remote | 0 | 0 | 0 | 0 | 0 | drug_interaction | image_recognition | edge_device | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 2,023 |
98 | district | rural | 1 | 0 | 0 | 0 | 0 | diabetic_retinopathy | predictive_model | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 2,021 |
99 | health_centre | urban | 0 | 1 | 1 | 0 | 0 | triage_severity | nlp | hybrid | 0 | 0 | 0 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 5 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 2,023 |
100 | community | rural | 0 | 0 | 0 | 0 | 0 | triage_severity | predictive_model | cloud | 0 | 0 | 1 | 0 | 0 | 0 | 0 | na | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 3 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 2,021 |
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⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.
AI & Clinical Decision Support
Abstract
Synthetic dataset modeling AI and clinical decision support system deployment across three SSA scenarios. Captures AI domains (TB CXR, retinopathy, triage), deployment modes, recommendation adherence, diagnostic accuracy, provider trust, validation status, barriers, and safety metrics. Parameterized from SSA AI health research.
Parameterization Evidence
| Parameter | Value | Source | Year |
|---|---|---|---|
| Most SSA AI projects | Pilot stage | Wahl et al. BMJ Glob Health | 2018 |
| CDSS improves accuracy | 10-30% | Topol. Nat Med | 2019 |
| AI TB detection sensitivity | 90-98% | Mollura et al. Radiology | 2020 |
| Local validation critical | Bias concerns | Mollura et al. | 2020 |
Validation
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/ai-clinical-decision-support", name="ai_pilot")
df = ds['train'].to_pandas()
References
- Wahl B et al. (2018). AI global health. BMJ Glob Health. DOI: 10.1136/bmjgh-2018-000798
- Topol EJ (2019). High-performance medicine. Nat Med. DOI: 10.1038/s41591-018-0300-7
- Mollura DJ et al. (2020). AI radiology LMICs. Radiology. DOI: 10.1148/radiol.2020201434
License
CC-BY-4.0
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