- We have developed a scientific abstract generator, available at https://writemeanabstract.com/.
- Our abstract generator is powered by OpenAI’s GPT-2 model and fine-tuned on PubMed abstracts.
- In developing this model, we wanted to better understand GPT-2, as well as its strengths and limitations in understanding language from the biomedical domain.
Given title: Effect of garlic consumption in systemic lupus erythematosus.Generated abstractOBJECTIVES: To determine the effect of garlic consumption in systemic lupus erythematosus (SLE) and to evaluate the safety of garlic consumption. METHODS: This was a single-center, randomized, controlled clinical trial. We randomly assigned patients with SLE to receive garlic (G; n = 30) or placebo (P; n = 30) for 12 mo. The primary endpoint was the percentage of patients with an improvement of SLE activity (SLEDAI-2K), which is a composite measure of SLE activity.RESULTS: The G and P groups did not differ significantly at baseline or at 12 mo. At 12 mo, the G and P groups showed no difference in improvement of the SLEDAI-2K (mean difference -0.1, 95% CI: -2.4 to 2.4; P = 0.8). The G and P groups also had significant reductions in the number of adverse events (P < 0.001). No severe adverse events were recorded.CONCLUSIONS: In this study of SLE patients receiving G (n = 30) or P (n = 30), the consumption of garlic for 12 mo did not improve their disease or reduce adverse events compared with the control.
- The model can successfully follow its “train of thought” across sentences.
- It successfully learned abbreviations and sometimes generated new, meaningful ones.
- It learned to properly structure an abstract into sections, such as Objectives, Methods and Conclusions, as often found in biomedical abstracts. That could be interesting in terms of summarising or extracting factual data.
- It’s not that good at maths:
…The study was carried out with 1250 participants, of whom 728 and 743 were children and adults, respectively, from Spain…
- On multiple occasions, it understood ranges of numbers:
…We studied 12 patients with a median age of 44.8 years (range, 21.3–58.1 years); most patients were female (71.4%), were white (87.5%), and had a mean AP duration of 15.9 days (range, 8–23 days). CVVHF was performed for a median of 19.0 hours (range, 8–30.0 hours)….
- It can successfully come up with new drugs. Well, sort of:
Intravenous and intraperitoneal administration of nafenib improves muscle mass and function in rats with cerebral vasospasm.BACKGROUND: Nafenib, an oral, cytotoxic, cysteine-rich cysteine protease inhibitor, was tested in animal models of cerebral vasospasm by treating animals with nafenib intravascularly or intraparenterally.
- To fine-tune our model we used gpt-2-simple and to make the 774M model fit into our 16GB GPUs, we used the much useful comments on that Github issue.
- We tried different parameters, but eventually ended up with a learning rate of 2e-5, only one epoch pass over the data and a maximum sequence length of 256 (that was necessary due to 774 model’s memory restrictions).
- Fine-tuning on a sole GPU V100 16GB RAM took around 6 days.