sentence-transformers How to use bisectgroup/BiCA-small with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("bisectgroup/BiCA-small")
sentences = [
"Integrated health care for infectious diseases and non-communicable diseases in low-and middle-income countries",
"The purposes of this study were to create a new flow-chart of prehospital electrocardiography (ECG)-transmission, evaluate its predictive ability for ST-elevation myocardial infarction (STEMI) and shorten door-to-balloon time (DTBT). The new transmission flow-chart was created using symptoms from previous medical records of STEMI patients. A total of 4090 consecutive patients transferred emergently to our hospital were divided into two groups: those in ambulances with an ECG-transmission device with the new flow-chart (ECGT-FC) and those transferred without an ECG-transmission device (non-ECGT) groups. A STEMI group comprising walk-in patients during the same period was used as a control group. The predictive ability of STEMI and the effectiveness of shortening the DTBT by the new flow-chart of ECG-transmission was evaluated. In the ECGT-FC group, the prevalence of STEMI in the ECG-transmission by the new flow-chart were significantly higher than in the non-ECG-transmission patients (6.71% vs. 0.19%; p<0.001). The sensitivity and specificity of the new ECG-transmission flow-chart were 83.3% and 88.1%, respectively. The median DTBT was significantly shortened (p=0.045) and the prevalence of DTBT<90min was significantly higher in the ECGT-FC group (p=0.018) than the other groups. The sensitivity and specificity of the new flow-chart for ECG-transmission were high. The new flow-chart combined with an ECG-transmission device could detect STEMI efficiently and shorten DTBT.",
"Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number ",
"The co-occurrence of infectious diseases (ID) and non-communicable diseases (NCD) is widespread, presenting health service delivery challenges especially in low-and middle-income countries (LMICs). Integrated health care is a possible solution but may require a paradigm shift to be successfully implemented. This literature review identifies integrated care examples among selected ID and NCD dyads. We searched PubMed, PsycINFO, Cochrane Library, CINAHL, Web of Science, EMBASE, Global Health Database, and selected clinical trials registries. Eligible studies were published between 2010 and December 2022, available in English, and report health service delivery programs or policies for the selected disease dyads in LMICs. We identified 111 studies that met the inclusion criteria, including 56 on tuberculosis and diabetes integration, 46 on health system adaptations to treat COVID-19 and cardiometabolic diseases, and 9 on COVID-19, diabetes, and tuberculosis screening. Prior to the COVID-19 pandemic, most studies on diabetes-tuberculosis integration focused on clinical service delivery screening. By far the most reported health system outcomes across all studies related to health service delivery (n = 72), and 19 addressed health workforce. Outcomes related to health information systems (n = 5), leadership and governance (n = 3), health financing (n = 2), and essential medicines (n = 4)) were sparse. Telemedicine service delivery was the most common adaptation described in studies on COVID-19 and either cardiometabolic diseases or diabetes and tuberculosis. ID-NCD integration is being explored by health systems to deal with increasingly complex health needs, including comorbidities. High excess mortality from COVID-19 associated with NCD-related comorbidity prompted calls for more integrated ID-NCD surveillance and solutions. Evidence of clinical integration of health service delivery and workforce has grown-especially for HIV and NCDs-but other health system building blocks, particularly access to essential medicines, health financing, and leadership and governance, remain in disease silos."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
