Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach

Haolin Li; Shuyang Jiang; Ruipeng Zhang; Jiangchao Yao; Ya Zhang; Yanfeng Wang

cs.LGApr 13, 2026

Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach

Authors: Haolin Li, Shuyang Jiang, Ruipeng Zhang, Jiangchao Yao, Ya Zhang, Yanfeng Wang

Organizations: College of Computer Science and Artificial Intelligence, Fudan University · Shanghai AI Laboratory · Department of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine · CMIC, Shanghai Jiao Tong University ·

Abstract

While large language models hold promise for complex medical applications, their development is hindered by the scarcity of high-quality reasoning data. To address this issue, existing approaches typically distill chain-of-thought reasoning traces from large proprietary models via supervised fine-tuning, then conduct reinforcement learning (RL). These methods exhibit limited improvement on underrepresented domains like rare diseases while incurring substantial costs from generating complex reasoning chains. To efficiently enhance medical reasoning, we propose MedSSR, a Medical Knowledge-enhanced data Synthesis and Semi-supervised Reinforcement learning framework. Our framework first employs rare disease knowledge to synthesize distribution-controllable reasoning questions. We then utilize the policy model itself to generate high-quality pseudo-labels. This enables a two-stage, intrinsic-to-extrinsic training paradigm: self-supervised RL on the pseudo-labeled synthetic data, followed by supervised RL on the human-annotated real data. MedSSR scales model training efficiently without relying on costly trace distillation. Extensive experiments on Qwen and Llama demonstrate that our method outperforms existing methods across ten medical benchmarks, achieving up to +5.93% gain on rare-disease tasks. Our code is available at https://github.com/tdlhl/MedSSR.

Figures & tables

Figure 1: Distribution of question types in existing medical datasets. Only 22% are reasoning-intensive, and just 3% among them concern rare diseases.

Panel of Figure 2 — Figure 2: Left : Comparison of existing methods for medical reasoning. “SS RL” is short for self-supervised RL. “Avg Token/Sample” denotes the average number of tokens consumed from an API model to generate one sample. Right : Performance improvement comparison based on Llama. Prior methods show less improvement in rare diseases than common tasks, while ours significantly breaks the rare disease improvement upper bound of $+3\%$ .

Figure 3: Overview of the proposed method. We first synthesize questions with tunable distribution, then train the policy model via a semi-supervised reinforcement learning mechanism. Rare disease knowledge injection is triggered when the random value $\rho$ is less than the threshold $\alpha$ .

Model	Symptoms	Causes	Diagnosis	Others	RDs	Treatment	Affects	Avg
Large Language Models
Qwen3-8B	68.63	72.01	57.95	66.44	70.39	52.18	68.28	65.13
R1-Distill-Llama-8B	53.58	63.04	45.49	60.19	55.52	46.57	63.28	55.38
Medical Large Language Models
UltraMedical-3.1-8B	73.53	73.01	57.28	65.28	77.47	50.83	73.79	67.31
HuatuoGPT-o1-8B	74.90	78.47	61.64	70.10	79.53	52.89	78.68	70.89

Table 1: Performance on rare diseases. “RDs” is short for Related Disorders. The best results are in Bold .

\uparrow

denotes the relative improvement of our method compared to the fully-supervised baseline. Ours is highlighted in gray.

Model	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	Avg
Large Language Models
Qwen3-8B	75.32	62.14	66.22	15.91	83.20	48.00	61.48	63.77	48.86	58.32
R1-Distill-Llama-8B	69.82	46.42	46.60	6.28	65.24	47.30	42.08	48.36	31.66	44.86
Medical Large Language Models
UltraMedical-3.1-8B	81.42	60.75	64.61	13.46	75.16	58.08	64.84	60.14	51.06	58.84
HuatuoGPT-o1-8B	80.97	64.77	77.79	16.68	79.57	58.35	65.92	62.68	54.30	62.34

Table 2: Performance on general medical tasks. All results are the average of four runs.

Stage	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	Avg
One-stage	82.16	67.10	78.06	17.77	86.04	54.70	69.49	68.32	62.26	65.10
Reverse-stage-I	81.91	64.25	74.98	17.40	83.88	54.15	68.74	67.66	55.11	63.12
Reverse-stage-II	82.83	67.48	78.67	17.27	85.56	53.30	69.36	69.66	60.55	64.96
Two-stage-I	82.51	65.44	75.61	17.09	86.25	55.05	66.91	68.87	55.92	63.74
Two-stage-II	86.00	67.79	81.14	20.66	86.64	54.70	71.97	70.94	63.47	67.03

Table 3: Ablation on training strategy. “One-stage” denotes mixed training without separating synthetic/real data.

Figure 4: Average performance on rare disease and general datasets across different rare disease ratios.

Figure 5: Impact of rare disease knowledge injection. The upper/lower part denotes rare/general tasks.

Figure 6: Rewards (left) and performance (right) curves of different labeling strategies across training steps.

Group	Incorrect	Harmful	Plausibility
Senior	1/200	1/200	4.86/5
Junior	0/200	0/200	4.74/5
Overall	0.50%	0.50%	4.80/5

Table 4: Physician evaluation of synthetic samples.

Figure 7: Comparison of our question-only synthesis and long reasoning chain synthesis (SFT).

Appendix figures & tables18 assets

Supplementary material from the paper’s appendix.

Appendix

Group	# Sample	# Incorrect	# Harmful	# Rating	# SD
Senior	200	1	1	4.86	0.42
1	50	1	1	4.92	-
2	50	0	0	4.78	-
3	48	0	0	4.78	-
4	52	0	0	4.95	-
Junior	200	0	0	4.74	0.54

Appendix

Table 5: Physician evaluation results of synthetic data. “SD” denotes the standard deviation of the plausibility rating within the group.

Number	Incorrect	Harmful	Plausibility
200	0.50%	0.50%	4.80/5
300	1.00%	0.67%	4.88/5
500	4/500 (0.80%)	3/500 (0.60%)	4.85/5

Appendix

Table 6: Expanded Physician evaluation.

Dataset	# All	# Train	# Test	# Rare
BioASQ	1482	700	782	144
MedQA	11451	10178	1273	154
MedMCQA	184022	182822	1200	45
PubMedQA	1000	500	500	63
HeadQA	296	296	-	-
MedXpertqa	2450	-	2450	301

Appendix

Table 7: The statistics of the datasets.

Param	Qwen	Llama
Data Configuration
Global batch size	128	128
PPO mini batch size	128	128
PPO micro batch size	8	8
Max prompt length	1024	1024
Max response length	4096	4096

Appendix

Table 8: Detailed configuration for RL training.

Model	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	RareDis
Large Language Models
Qwen3-8B	1.90	0.23	1.33	0.36	1.08	1.19	0.68	0.54	1.31	0.41
R1-Distill-Llama-8B	2.08	0.88	1.31	0.64	1.61	1.63	1.59	0.88	2.51	0.40
Medical Large Language Models
UltraMedical-3.1-8B	1.13	0.97	1.15	0.70	1.31	1.15	0.35	1.64	1.06	0.64
HuatuoGPT-o1-8B	1.42	0.21	0.18	0.58	1.00	0.92	1.05	1.12	0.62	0.31

Appendix

Table 9: Detailed standard deviations across all models and benchmarks.

Figure 8: Rewards and performance curves of offline labeling with more than 1K steps. We report the average performance on test sets with error bars.

Ratio	Symptoms	Causes	Diagnosis	Others	RDs	Treatment	Affects	Avg
0%	73.73	77.76	63.07	70.37	71.22	55.84	76.38	69.77
13%	76.57	77.49	64.89	72.69	74.51	55.57	76.03	71.11
25%	79.71	80.89	68.19	72.22	76.64	57.51	78.62	73.40
33%	78.14	78.49	68.33	75.93	79.77	59.60	80.52	74.40
50%	79.12	78.62	65.84	72.45	78.78	58.63	78.45	73.13

Appendix

Table 10: Performance on RareDis-Sub across different rare disease ratios. “RDs” is short for Related Disorders.

Ratio	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	Avg
0%	83.47	65.89	75.69	16.40	84.53	55.20	67.50	67.59	56.09	63.60
13%	84.78	68.73	82.54	21.27	87.21	56.20	70.56	69.78	64.12	67.24
25%	86.00	67.79	81.14	20.66	86.64	54.70	71.97	70.94	63.47	67.03
33%	83.38	68.56	81.38	20.97	86.13	53.55	71.39	67.72	64.86	66.44
50%	84.14	67.50	80.20	19.42	86.36	56.15	69.32	66.99	64.45	66.06

Appendix

Table 11: Performance on general medical datasets across different rare disease ratios.

Data Scale	Method	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	Avg
$\times 1$	Fully-supervised	81.91	64.25	74.98	17.40	83.88	54.15	68.74	67.66	55.11	63.12
$\times 1$	Self-supervised	82.51	65.44	75.61	17.09	86.25	55.05	66.91	68.87	55.92	63.74
$\times 2$	Fully-supervised	81.40	66.79	77.36	16.97	84.78	55.05	69.03	68.14	58.60	64.24
$\times 2$	MedSSR	86.00	67.79	81.14	20.66	86.64	54.70	71.97	70.94	63.47	67.03

Appendix

Table 12: Performance across nine datasets under similar training cost. We define “×1 scale” as the 43K data volume used in prior experiments. The results of both “×1 scale” and “×2 scale” experiments are reported for comparison.

Model	Symptoms	Causes	Diagnosis	Others	RDs	Treatment	Affects	Avg
Qwen3-1.7B-Base	37.35	46.65	34.03	40.05	37.17	33.77	35.86	37.84
+ MedSSR	49.71	55.43	44.81	48.84	49.84	40.35	47.24	48.03
$\uparrow$	12.36	8.78	10.78	8.79	12.67	6.58	11.38	10.19
Qwen3-4B-Base	60.29	66.80	48.99	58.80	53.62	45.73	63.97	56.89
+ MedSSR	70.69	75.14	58.69	68.29	70.23	53.76	72.41	67.03
$\uparrow$	10.40	8.34	9.70	9.49	16.61	8.03	8.44	10.14

Appendix

Table 13: Performance on RareDis-Sub across different LLM scales. “RDs” is short for Related Disorders.

Model	BioASQ	MedMCQA	MedQA	MedXpertqa	MMLU	PubMedQA	NEJM	Lancet	Medbullets	Avg
Qwen3-1.7B-Base	56.10	41.36	39.20	11.58	53.81	45.35	37.94	32.16	30.20	38.63
+ MedSSR	71.99	48.17	46.86	12.54	61.85	49.05	48.84	46.66	38.48	47.16
$\uparrow$	15.89	6.81	7.66	0.96	8.04	3.70	10.90	14.50	8.28	8.53
Qwen3-4B-Base	76.53	52.44	55.58	11.87	74.03	50.20	54.39	52.49	41.56	52.12
+ MedSSR	82.61	63.86	72.25	16.54	81.96	54.05	65.30	64.14	57.47	62.02
$\uparrow$	6.08	11.42	16.67	4.67	7.93	3.85	10.91	11.65	15.91	9.90

Appendix

Table 14: Performance on general medical datasets across different LLM scales.

Case Study w/ rare disease
Seed Question 1	An army recruit, smoker and 6 months into training staed complaining of pain at postero medial aspect of both legs. There was acute point tenderness and the pain was aggravated on physical activity. The most likely diagnosis is A. Bearger’s disease B. Gout C. Lumbar canal stenosis D. Stress fracture
Seed Question 2	A patient presenting with haemoptysis and renal failure with antibasement membrane antibodies has - A. Good pasture’s B. Wegener’s C. Churg Strauss D. Henoch-schonlein purpura
Rare Disease	Worster-Drought syndrome/Suprabulbar paresis, congenital
Retrieved Knowledge	Worster-Drought syndrome is a form of congenital suprabulbar paresis that occurs in some children with cerebral palsy. It is caused by inadequate development of the corticobulbar tracts and causes problems with the mouth and tongue including impaired swallowing. A similar syndrome in adults is called anterior opercular syndrome. A 1986 study of a family in which multiple members had Worster-Drought syndrome suggested it might be hereditary. A 2000 review of cases classified Worster-Drought Syndrome as a form of cerebral palsy, caused by early damage to the brain, but identified no obvious causes during gestation or birth and found some families with a history of the condition. The syndrome was named after Cecil Charles Worster-Drought , the doctor who described it in 1956.
Synthetic Question	A 5-year-old child presents with significant speech delay, difficulty swallowing since infancy, and drooling. Neurological examination reveals impaired movement of the tongue and soft palate, with no limb weakness. The child’s mother reports similar symptoms in her own childhood. MRI shows underdevelopment of the corticobulbar tracts. Which of the following is the most likely diagnosis? A. Moebius syndrome B. Spinal muscular atrophy (bulbar form) C. Worster-Drought syndrome D. Anterior opercular syndrome (acquired suprabulbar palsy)
Majority Answer Num: 5/8	To determine the most likely diagnosis for this 5-year-old child, let’s go through the information step-by-step. ### Step-by-Step Analysis: 1. Clinical Presentation: - Significant speech delay - Difficulty swallowing since infancy - Drooling - Impaired movement of the tongue and soft palate - No limb weakness. 2. Family History: - Similar symptoms in the mother2̆019s childhood. 3. Neurological Examination: - Impaired movement of the tongue and soft palate - No limb weakness. 4. Imaging Findings: - MRI shows underdevelopment of the corticobulbar tracts. ### Differential Diagnosis: 1. Moebius Syndrome (A): - Characterized by congenital facial paralysis (including inability to move the eyes laterally and the mouth) and sometimes other cranial nerve abnormalities. - Often associated with feeding difficulties, facial asymmetry, and small eyes. - Does not typically involve limb weakness or underdevelopment of the corticobulbar tracts. 2. Spinal Muscular Atrophy (Bulbar Form) (B): - Typically presents with muscle weakness and wasting, particularly in the bulbar muscles (speech, swallowing, and respiratory muscles). - Often has a progressive course. - Usually involves limb weakness due to lower motor neuron involvement. 3. Worster-Drought Syndrome (C): - Also known as congenital central hypoventilation syndrome. - Characterized by underdevelopment of the brainstem, particularly the pontine respiratory centers. - May present with respiratory issues, but not typically with speech delay or swallowing difficulties unless it affects the cranial nerves. - Usually involves other neurological symptoms like poor sucking and feeding. 4. Anterior Opercular Syndrome (D): - Also known as acquired suprabulbar palsy. - Caused by lesions affecting the corticobulbar tracts, leading to weakness or paralysis of the muscles supplied by the lower motor neurons (e.g., facial, tongue, and pharyngeal muscles). - Typically presents in adults, not children. - Associated with spasticity and hyperreflexia due to upper motor neuron involvement. ### Final Considerations: - The combination of significant speech delay, difficulty swallowing since infancy, drooling, impaired movement of the tongue and soft palate, and underdevelopment of the corticobulbar tracts suggests a congenital condition affecting the brainstem and cranial nerves. - The presence of similar symptoms in the mother2̆019s childhood suggests a familial pattern, which is characteristic of Worster-Drought syndrome or Moebius syndrome. Given the specific combination of symptoms and imaging findings, Worster-Drought syndrome (also known as congenital central hypoventilation syndrome with associated craniofacial anomalies) is the most likely diagnosis. This condition is characterized by underdevelopment of the brainstem, which would explain the underdevelopment of the corticobulbar tracts and the associated cranial nerve abnormalities. ### Final Answer: The final answer is C.

Appendix

Table 15: Case study with rare disease knowledge injection in data synthesis.

Case Study w/o rare disease
Seed Question 1	A 35wks POG, USG parameters more or less corresponding to POG. Doppler showing absent end diastolic flow Management: A. Monitor till it becomes reverse diastolic flow or 37 weeks B. Monitor till 37 weeks C. Give steroids and wait for 48 hours D. Plan for immediate termination
Seed Question 2	A drug ’X’ belongs to the anticholinergic drug group. It is primarily used in pre anesthetic medication and also during surgery. Which of the following can be ’X’ ? A. Glycopyrrolate B. Pipenzolate methyl bromide C. Isopropamide D. Dicyclomine
Synthetic Question	A 32-year-old woman at 33 weeks gestation presents with reduced fetal movements. Ultrasound reveals an estimated fetal weight below the 10th percentile for gestational age. Umbilical artery Doppler shows an elevated systolic/diastolic ratio but preserved end-diastolic flow. Non-stress test is non-reactive. What is the most appropriate next step in management? A. Repeat non-stress test in 24 hours and continue monitoring B. Administer corticosteroids and plan delivery after 48 hours C. Immediate delivery D. Start magnesium sulfate and continue pregnancy until 37 weeks
Majority Answer Num: 6/8	# Step-by-step reasoning: 1. Clinical Presentation: - The patient is a 32-year-old woman at 33 weeks gestation. - She presents with reduced fetal movements, which is concerning for fetal compromise. - Ultrasound reveals an estimated fetal weight below the 10th percentile for gestational age, indicating fetal growth restriction (FGR). - Umbilical artery Doppler shows an elevated systolic/diastolic ratio but preserved end-diastolic flow, suggesting chronic placental insufficiency but not acute compromise. - The non-stress test is non-reactive, which is abnormal and indicates reduced fetal reactivity. 2. Interpretation of Findings: - Reduced fetal movements and estimated fetal weight below the 10th percentile are strong indicators of fetal growth restriction (FGR). - Elevated systolic/diastolic ratio on umbilical artery Doppler suggests chronic placental insufficiency. - Preserved end-diastolic flow indicates that there is still some placental function, but it is compromised. - A non-reactive non-stress test is abnormal and suggests reduced fetal reactivity, which is concerning for fetal distress. 3. Management of FGR with Abnormal Non-Stress Test: - In cases of FGR with abnormal non-stress tests (e.g., non-reactive), the next step is to assess for acute fetal compromise. - If there is evidence of acute fetal distress (e.g., abnormal biophysical profile, abnormal Doppler findings), immediate delivery may be indicated. - In the absence of acute distress, the decision to deliver depends on the gestational age, fetal condition, and maternal factors. 4. Gestational Age and Decision Making: - At 33 weeks gestation, the fetus is considered preterm. - If there is no evidence of acute fetal distress, delivery is generally not indicated unless there is clear evidence of worsening fetal condition. - Corticosteroids may be administered to promote fetal lung maturity if delivery is likely within 7 days. 5. Most Appropriate Next Step: - Given the reduced fetal movements, FGR, and abnormal non-stress test, the next step should be to assess for acute fetal distress. - If there is no evidence of acute distress, corticosteroids should be administered to promote fetal lung maturity, and the patient should be monitored closely for further fetal deterioration. - Delivery is typically not indicated at 33 weeks unless there is clear evidence of acute fetal distress or worsening fetal condition. 6. Final Decision: - Administer corticosteroids to promote fetal lung maturity. - Plan delivery after 48 hours if there is no improvement in fetal condition or if there is evidence of acute fetal distress. # Final Answer: The final answer is B.
Minority Answer Num: 2/8	To determine the most appropriate next step in the management of a 32-year-old woman at 33 weeks gestation with reduced fetal movements, let’s break this down step-by-step. ### Step-by-Step Reasoning: 1. Clinical Presentation: - The patient is at 33 weeks gestation. - She presents with reduced fetal movements. - Ultrasound reveals an estimated fetal weight below the 10th percentile for gestational age (indicating intrauterine growth restriction, IUGR). - Umbilical artery Doppler shows an elevated systolic/diastolic ratio but preserved end-diastolic flow (suggesting chronic placental insufficiency). - Non-stress test is non-reactive (indicating poor fetal well-being). 2. Interpretation of Findings: - Reduced fetal movements + IUGR + abnormal Doppler + non-reactive NST suggest fetal compromise. - Elevated systolic/diastolic ratio indicates chronic placental insufficiency, which is often associated with poor outcomes if not addressed promptly. 3. Management Considerations: - Intrauterine growth restriction (IUGR) with abnormal Doppler findings and non-reactive NST is concerning for fetal compromise. - Immediate intervention may be necessary to prevent adverse outcomes such as stillbirth or neonatal morbidity. 4. Options Analysis: - A: Repeat non-stress test in 24 hours and continue monitoring - This is not appropriate given the presence of non-reactive NST and other concerning findings. - B: Administer corticosteroids and plan delivery after 48 hours - Corticosteroids can be given to promote fetal lung maturity, but immediate delivery might be warranted based on the findings. - C: Immediate delivery - Given the combination of reduced fetal movements, IUGR, abnormal Doppler, and non-reactive NST, immediate delivery is often recommended to prevent further fetal compromise. - D: Start magnesium sulfate and continue pregnancy until 37 weeks - Magnesium sulfate is typically used for neuroprotection in preterm labor, not for managing IUGR with compromised fetal status. 5. Final Decision: - The presence of non-reactive NST and IUGR with abnormal Doppler findings suggests significant fetal compromise. - Immediate delivery is generally recommended in such cases to prevent adverse outcomes. ### Final Answer: Given the clinical presentation and findings, the most appropriate next step in management is immediate delivery. Therefore, the final answer is C.

Appendix

Table 16: Case study without rare disease knowledge injection in data synthesis.

Failure Case
Question	A 55-year-old woman presents with progressive weakness in her right hand and difficulty manipulating small objects over the past 3 months. She also reports mild pain radiating from her neck to her right shoulder. On examination, there is atrophy of the right thenar muscles and decreased sensation over the lateral aspect of the right hand. What is the most likely diagnosis?
Options	A. Carpal tunnel syndrome, B. Cervical radiculopathy (C6-C7), C. Ulnar nerve entrapment at the elbow, D. Thoracic outlet syndrome.
Ground Truth	A. Carpal tunnel syndrome
Voting Results	"A": 0, "B": 8, "C": 0, "D": 0
Response Example	To determine the most likely diagnosis for this patient, let’s break it down step-by-step: ### Step-by-Step Reasoning: 1. Clinical Presentation: - Age: 55 years old - Symptoms: Progressive weakness in the right hand, difficulty manipulating small objects, mild pain radiating from the neck to the right shoulder - Physical Exam: Atrophy of the right thenar muscles, decreased sensation over the lateral aspect of the right hand 2. Key Findings: - Atrophy of the thenar muscles: This is characteristic of median nerve involvement. - Decreased sensation over the lateral aspect of the right hand: The lateral aspect of the hand is innervated by the radial nerve, but the thenar muscles are primarily innervated by the median nerve. - Radiating pain from the neck to the shoulder: This suggests a cervical spine issue rather than a peripheral nerve problem. 3. Differential Diagnosis: - A: Carpal Tunnel Syndrome: Typically presents with numbness and tingling in the thumb, index, middle, and half of the ring finger, but usually not with thenar muscle atrophy or neck pain . - B: Cervical Radiculopathy (C6-C7): Commonly presents with weakness in the wrist extensors (extensor carpi radialis brevis, extensor carpi radialis longus, and extensor carpi ulnaris), which can cause difficulty with small object manipulation. It also often involves pain radiating from the neck to the shoulder, and sensory changes in the thumb, index, and middle fingers (C6) or the middle and ring fingers (C7). Thenar muscle atrophy is more commonly associated with C7 radiculopathy. - C: Ulnar Nerve Entrapment at the Elbow: Presents with weakness in the hypothenar muscles, adductor pollicis, and interossei, along with decreased sensation in the little finger and half of the ring finger. There is no significant atrophy of the thenar muscles. - D: Thoracic Outlet Syndrome: Can present with symptoms similar to those of cervical radiculopathy, including pain, numbness, and weakness in the upper extremity, but typically involves both arms and may be associated with vascular signs like cyanosis or pallor of the hand. 4. Specificity of Symptoms: - Thenar muscle atrophy is strongly suggestive of median nerve involvement, which is often due to compression at the wrist (carpal tunnel syndrome) or cervical spine issues (e.g., C6 or C7 radiculopathy). - Radiating pain from the neck to the shoulder points towards a cervical spine origin. - Lateral aspect of the hand is not typically affected by median nerve issues but could be related to radial nerve issues, which are less likely given the presence of thenar muscle atrophy. 5. Conclusion: - The combination of thenar muscle atrophy, decreased sensation over the lateral aspect of the hand, and radiating pain from the neck to the shoulder is most consistent with C6-C7 cervical radiculopathy. - The lateral aspect of the hand is innervated by the radial nerve, which can be affected by C6 radiculopathy, but the presence of thenar muscle atrophy points more strongly to C7 involvement. ### Final Answer: Based on the clinical presentation and physical exam findings, the most likely diagnosis is B: Cervical radiculopathy (C6-C7). The final answer is B"

Appendix

Table 17: Failure case analysis of majority-voted labels. The incorrect parts are highlighted in red .

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