Large language models (LLMs), such as GPT3.5, GPT4 and LLAMA2 perform surprisingly well and outperform human experts on many tasks. However, in many domain-specific evaluations, these LLMs often suffer from hallucination problems due to insufficient training of relevant corpus. Furthermore, fine-tuning large models may face problems such as the LLMs are not open source or the construction of high-quality domain instruction is difficult. Therefore, structured knowledge databases such as knowledge graph can better provide domain background knowledge for LLMs and make full use of the reasoning and analysis capabilities of LLMs. In some previous works, LLM was called multiple times to determine whether the current triplet was suitable for inclusion in the subgraph when retrieving subgraphs through a question. Especially for the question that require a multi-hop reasoning path, frequent calls to LLM will consume a lot of computing power. Moreover, when choosing the reasoning path, LLM will be called once for each step, and if one of the steps is selected incorrectly, it will lead to the accumulation of errors in the following steps. In this paper, we integrated and optimized a pipeline for selecting reasoning paths from KG based on LLM, which can reduce the dependency on LLM. In addition, we propose a simple and effective subgraph retrieval method based on chain of thought (CoT) and page rank which can returns the paths most likely to contain the answer. We conduct experiments on three datasets: GenMedGPT-5k [14], WebQuestions [2], and CMCQA [21]. Finally, RoK can demonstrate that using fewer LLM calls can achieve the same results as previous SOTAs models.

Chronic pain is a pervasive disorder which is often very disabling and is associated with comorbidities such as depression and anxiety. Neuropathic Pain (NP) is a common sub-type which is often caused due to nerve damage and has a known pathophysiology. Another common sub-type is Fibromyalgia (FM) which is described as musculoskeletal, diffuse pain that is widespread through the body. The pathophysiology of FM is poorly understood, making it very hard to diagnose. Standard medications and treatments for FM and NP differ from one another and if misdiagnosed it can cause an increase in symptom severity. To overcome this difficulty, we propose a novel framework, PainPoints, which accurately detects the sub-type of pain and generates clinical notes via summarizing the patient interviews. Specifically, PainPoints makes use of large language models to perform sentence-level classification of the text obtained from interviews of FM and NP patients with a reliable AUC of 0.83. Using a sufficiency-based interpretability approach, we explain how the fine-tuned model accurately picks up on the nuances that patients use to describe their pain. Finally, we generate summaries of these interviews via expert interventions by introducing a novel facet-based approach. PainPoints thus enables practitioners to add/drop facets and generate a custom summary based on the notion of "facet-coverage" which is also introduced in this work.

Scientists have found a correlation between a disease involving chronic pain and alterations in the gut microbiome. Fibromyalgia affects 2-4 percent of the population and has no known cure. Symptoms include fatigue, impaired sleep and cognitive difficulties, but the disease is most clearly characterized by widespread chronic pain. In a paper published today in the journal Pain, a Montreal-based research team has shown, for the first time, that there are alterations in the bacteria in the gastrointestinal tracts of people with fibromyalgia. Approximately 20 different species of bacteria were found in either greater or are lesser quantities in the microbiomes of participants suffering from the disease than in the healthy control group.

When Ginevra Liptan came back to medical school after a year's leave, she told her favorite professor she'd taken time off to deal with the onset of fibromyalgia. "He rolled his eyes and said, 'That doesn't exist,'" says Liptan. In the 16 years since Liptan had her illness so summarily dismissed in 2002, there are still those who believe fibromyalgia isn't "real." There's no tissue damage that explains the pain fibromyalgia patients experience all over their body, and contemporary medicine struggles to treat and even accept an illness where pain seems to be rooted in the mind or brain, rather than a bodily injury. Patients typically see upwards of 10 specialists before they're diagnosed with fibromyalgia, says Liptan, who is now a doctor and founder of the The Frida Center for Fibromyalgia in Portland, Oregon (the center is named for the artist Frida Kahlo, who some doctors and art historians believe suffered from fibromyalgia).