Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Purpose: To report a case of paraneoplastic autoimmune retinopathy in a patient with a history of testicular cancer.Case summary: A 29-year-old man presented with photopsia and floaters. Initial fundus examination revealed no abnormal findings. However, he returned 1 month later with complaints of visual field defects. Fundus examination revealed diffuse white spots in the macula and midperipheral retina and fundus autofluorescence demonstrated hyper-autofluorescence. Optical coherence tomography showed disruption of the ellipsoid zone sparing the fovea. Visual field examination revealed peripheral visual field defects and an electroretinogram showed reduced rod and cone cell responses. Considering his history of testicular cancer, serum paraneoplastic autoantibody panel testing was performed which revealed borderline levels of anti-recoverin antibody leading to a diagnosis of paraneoplastic autoimmune retinopathy. The patient was treated with oral steroids and mycophenolate mofetil for 1 year. However, there was no improvement in the subjective symptoms or ophthalmologic findings. Conclusions This case of paraneoplastic autoimmune retinopathy in a young man with a history of testicular cancer highlights an early clinical presentation of the disease. It is crucial to recognize that the initial clinical presentation of autoimmune retinopathy can be nonspecific.

Purpose: To report a case of paraneoplastic autoimmune retinopathy in a patient with a history of testicular cancer.Case summary: A 29-year-old man presented with photopsia and floaters. Initial fundus examination revealed no abnormal findings. However, he returned 1 month later with complaints of visual field defects. Fundus examination revealed diffuse white spots in the macula and midperipheral retina and fundus autofluorescence demonstrated hyper-autofluorescence. Optical coherence tomography showed disruption of the ellipsoid zone sparing the fovea. Visual field examination revealed peripheral visual field defects and an electroretinogram showed reduced rod and cone cell responses. Considering his history of testicular cancer, serum paraneoplastic autoantibody panel testing was performed which revealed borderline levels of anti-recoverin antibody leading to a diagnosis of paraneoplastic autoimmune retinopathy. The patient was treated with oral steroids and mycophenolate mofetil for 1 year. However, there was no improvement in the subjective symptoms or ophthalmologic findings. Conclusions This case of paraneoplastic autoimmune retinopathy in a young man with a history of testicular cancer highlights an early clinical presentation of the disease. It is crucial to recognize that the initial clinical presentation of autoimmune retinopathy can be nonspecific.

Purpose: To report a case of paraneoplastic autoimmune retinopathy in a patient with a history of testicular cancer.Case summary: A 29-year-old man presented with photopsia and floaters. Initial fundus examination revealed no abnormal findings. However, he returned 1 month later with complaints of visual field defects. Fundus examination revealed diffuse white spots in the macula and midperipheral retina and fundus autofluorescence demonstrated hyper-autofluorescence. Optical coherence tomography showed disruption of the ellipsoid zone sparing the fovea. Visual field examination revealed peripheral visual field defects and an electroretinogram showed reduced rod and cone cell responses. Considering his history of testicular cancer, serum paraneoplastic autoantibody panel testing was performed which revealed borderline levels of anti-recoverin antibody leading to a diagnosis of paraneoplastic autoimmune retinopathy. The patient was treated with oral steroids and mycophenolate mofetil for 1 year. However, there was no improvement in the subjective symptoms or ophthalmologic findings. Conclusions This case of paraneoplastic autoimmune retinopathy in a young man with a history of testicular cancer highlights an early clinical presentation of the disease. It is crucial to recognize that the initial clinical presentation of autoimmune retinopathy can be nonspecific.

A wild Whooper swan (Cygnus Cygnus) with limping due to an injured left pelvic limb in an accident was rescued on the seashore and transferred to the Jeju Wildlife Rescue Center on November 23rd, 2020. On physical examination, its body condition score was 1 out of 5 due to starvation and dehydration.The left coxofemoral joint was also examined by careful palpating and estimating the damage. Moderated soft tissue swelling and crepitus surrounding the hip joint were confirmed. Radiography and computed tomography (CT) were used together for an accurate diagnosis of the joint. By radiographs readings, it was difficult to accurately confirm the condition of the proximal femur due to superimposition of the synsacrum and internal organs. However, signs such as avulsion fracture of the femoral head and a few fragments around the joint were revealed by CT imaging. Besides, through three-dimensional (3D) image analysis of CT, the dislocated area and condition of the left hip joint could be accurately and easily confirmed. The diagnostic process showing in this paper could be used as a good reference for diagnosing coxofemoral joint luxation in wild swan.